Professor Yang Gao
Professor Yang Gao is the Professor of Space Autonomous Systems at Surrey Space Centre and Founding Head of the STAR LAB that specializes in robotic sensing, perception, visual GNC and biomimetic mechanisms for industrial applications in the extreme environments. She brings over 20 years of research experience in developing robotics and autonomous systems, in which she has been the Principal Investigator of inter/nationally teamed projects funded by UK Research Innovation (EPSRC/STFC/InnovateUK), Royal Academy of Engineering, European Commission, European Space Agency (ESA), UK Space Agency, as well as industry such as BT, Airbus, Neptec, Sellafield and OHB. Yang is also actively involved in design and development of real-world space missions including ESA ExoMars, Proba3 and VMMO (lunar ice mapper), UK MoonLITE/Moonraker, and CNSA Chang'E3. Yang's work has also been applied to several non-space sectors including nuclear, oil/gas and agriculture through technology transfer and spin offs.
Yang is the elected Fellow of Institute of Engineering and Technology (IET) and Royal Aeronautical Society (RAeS). She had been named by the Times Higher Education as one of ten young leading academics in the UK who are making a very significant contribution to their disciplines in 2008, and also been awarded the Mulan Award for Contributions to Science, Technology and Engineering in 2019. Research work under her leadership and supervision has received many international recognition, including International Astronautical Federation (IAF) 3AF Edmond Brun Silver Medal in 2013, COSPAR Outstanding Paper Award in 2016, UKSEDS Lunar Rover Competition First Prize in 2017, joint Winner of ESA SysNova Challenge on Lunar CubeSat Exploration in 2018, IEEE/ASME-AIM Best Paper Award Finalist in 2019, Top 3 place worldwide in ESA/Stanford Pose Estimation Challenge in 2019, and First Prize of Wiley Poster Award at IEEE-ICRA Space Workshop in 2020.
Yang has edited and co-authored 2 textbooks (by Wiley-VCH and by IET), 1 research book by McGraw-Hill, 1 proceeding book by Springer, and co-authored over 160 scientific papers in internationally refereed books, journals and conference proceedings. She is the Editor-in-Chief of Wiley Journal of Field Robotics, the Section Editor, Associate Editor or Guest Editor of other international journals (such as Springer's Current Robotics Reports, Frontiers' Robotics and AI, IEEE-CIM, and IEEE-AESM), and the Member of Technical Committees (such as IMechE Engage in Space Committee, IEEE-CIS and -RAS Technical Committees and Task Force).
Yang was the Conference General Chair of TAROS-2017 (the longest running UK-hosted international conference on AI robotics), the Conference Co-Chair of Light Conference 2018, the Conference Publicity Co-Chair of IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM-2019), and the Invited Speaker or Session Chair or of scientific conferences and seminars (such as ESA AI-STAR, IEEE-UK/Ireland RAS Prestigious Lecture, IEEE ICRA-Space Workshop, IEEE-CDC, iSAIRAS, UK Space Conference, World Congress of Robotics, IET Seminars, UK-RAS International Robotics Showcase, EMSTA Prestige Seminar, UK Astrobiology and Planetary Exploration Series, RiTA, etc).
Yang serves major funding review panels or committees for UKRI Future Leadership Fellowship, European Science Foundation, and Royal Society International Newton Fellowship, etc. She is also the Mentor for the Mulan Foundation as well as the United Nations Office for Outer Space Affairs (UNOOSA) Space4Women program.
Prior to joining SSC in 2004, Yang was an awardee of the prestigious Singapore Millennium Foundation (SMF) Postdoctoral Fellowship and worked on intelligent and autonomous vehicles. She gained the B.Eng. (First Class Honors) degree and Ph.D. degree from the Nanyang Technological University (NTU), Singapore in 2000 and 2003 respectively.
Areas of specialism
University roles and responsibilities
- Associate Dean (International) for Faculty of Engineering & Physical Sciences (10/2016-01/2021)
- Chair of Faculty International Relations Committee & Mobility Committee (10/2016-01/2021)
- Member of University External Engagement Committee (10/2016-01/2021)
Affiliations and memberships
In the media
Yang is actively involved in space mission design and promoting the Surrey 'small-sat' engineering approach within missions like ExoMars, Proba3, MoonLITE and Moonraker, etc. In recent years, Yang's work has also been applied to several non-space sectors including nuclear and agriculture.
The following research topics have been undertaken within the STAR LAB by Postdoc, PhD, MSc/UG project students. New PhD applications are still welcome to develop the relevant technologies to the next step. See STAR LAB page and FAIR-SPACE Hub page.
Spacecraft metrology & GNC
This topic of research aims to achieve high accuracy measurements for future spacecraft hence autonomous GNC in next-generation mission concepts ranging from formation flying to planetary exploration. We focuses on using optical and laser based instruments, developing 'space-friendly' cognitive visual saliency techniques and GNC algorithms for SLAM, terrain assessment, rendezvous and docking, etc. Existing projects include UKRI/UKSA FAIR-SPACE project, InnovateUK funded work on space metrology, Airbus DS funded study on next-generation rover and lander GNC, STFC-funded study on planetary rover technologies, ESA ExoMars PanCam study, EU FP7 project on Planetary Robotics Vision Ground Processing (PROVISG), RAEng funded project on lunar rover GNC for Chang’E mission, and SSTL Magnolia-1 project on precision lander autonomy, etc.
This research topic focus on developing domain-independent reconfigurable software architectures for future autonomous systems. It builds on autonomous software agents with abilities to learning and reason. Such technologies are particularly useful to address issues like decision-making, task planning and scheduling for growingly complex systems and to support future manned and unmanned space missions, as well as other industrial domains such as energy and agriculture. Existing projects include UKRI/UKSA FAIR-SPACE project, Sellafield funded project on autonomous operation of alpha plant, EPSRC-funded collaborative projects through its AISP, IAA programs and Strategic Collaboration Award, STFC funded project on autonomous vehicles for agriculture, and EU FP7 project on Forward Acquisition of Soil Terrain using Exploration Rovers (FASTER), etc.
Planetary drilling, sampling and resource utilization
This research topic focuses on developing low-energy drilling techniques for planetary subsurface sampling and scientific experiments (such as thermal conductivity, water and organics detection) within future planetary explorations. Main research inspirations are drawn from by nature where insects such as female wood wasps and female locusts use their ovipositor valves to drill into trees or soil to lay eggs. UKRI, UKSA, ESA and European industry such as OHB have been funding us to develop theoretical models and engineering prototypes.
Micro space vehicles: Rovers, penetrators
This research topic aims to design and develop low mass, low volume and low power space systems for low-cost planetary missions, which should provide excellent platforms for space autonomy. Development of a micro-rover would include chassis design, autonomous navigation and locomotion control. Existing studies include ESA ExoMars Phase-A study and RCET on chassis design covered traction analysis using Bekker theory, mean free path analysis based on rock distribution and rover mobility evaluation software (incl. 3D simulation). In terms of developing micro-penetrators, our lab is a major partner of UK penetrator consortium consisting of over 15 partners globally and has also been funded by Airbus DS to develop low-cost GNC solutions for micro-penetrators.
Missions to the moon, mars and beyond
We have been involved in design and development of future mission concepts such as low-cost UK lunar mission MoonLITE & Moonraker, commercially driven Lunar Mission One (LM-1), ESA proposals on EJMS, Marco Polo-R and GRESE, etc. We also supports payload development and data processing of missions like the Chinese Chang'E-3, ESA's Proba-3, LunaResurs, etc.
- Space agencies: NASA (JPL/Ames), ESA (ESTEC/ESOC), CNSA (CAST/SAST), DLR (Berlin/Bremen)
- Industrial companies: Airbus DS (UK, France, Germany, Poland), Neptec, BAE Systems, Sellafield, NNL, OHB/Kayser Threde
- Universities and institutes: UK (Imperial, UCL, Liverpool, Warwick, Sheffield, Edinburgh, AU Wales, Salford, Strathclyde), France (ISAE), Germeny (TU Berlin, TU Dresden, TU Darmstadt, DFKI), Austria (JR), USA (Ohio SU, MSU), China (CAS, HIT, BJUT, Beihang)
Indicators of esteem
Research Grants (net value £10m out of £15m worth of funding program):
- Research Councils and Government Agencies: EPSRC (2017-2021, 2016-2017, 2012-2016, 2012-2013); STFC (2014-2016, 2006-2007); InnovateUK (2017-2021, 2015-2018); NDA (2016-2020); RAEng (2015-2016; 2011-2012; 2008-2009); EU FP7 (2011-2014; 2008-2012); FCO (2007-2008).
- Space Agencies: UKSA (2017-2021, 2016-2017, 2015-2016); ESA (2019-2020, 2017-2018, 2008-2011);
- Industrial Companies: BT (2020-2021); CAS-CIOMP (2018-2021); Airbus D&S (2017-2019, 2013-2019; 2009-2012); Sellafield (2014-2018); OHB/Kayser-Threde (2014-2017); SSTL (2007-2008).
- Fellowships & Scholarships: SCEPTrE Fellowship (2010-2011); SMF Fellowship (2002-2004); NTU Scholarship for PhD Research (2000-2002); Singapore Ministry of Education Scholarship for Undergraduate Study (1996-2000).
- First Prize of Wiley Best Poster Award at IEEE-ICRA Space Robotics Workshop, 2020 (one of two co-authors and supervisor)
- Mulan Award for contributions to Science, Technology and Engineering, 2019
- Finalist of IEEE/ASME's AIM Best Paper Award, 2019 (one of three co-authors and supervisor)
- Top 3 Place for ESA/Stanford Pose Estimation Challenge, 2019 (supervisor)
- Joint Winner of ESA SysNova Challenge on Lunar CubeSat Exploration, 2018 (UK PI)
- First Prize of UKSEDS Lunar Rover Competition, 2017 (supervisor)
- COSPAR Outstanding Paper Award, 2016 (one of two co-authors and supervisor)
- International Astronautical Federation (IAF) 3AF Edmond Brun Silver Medal - supervisor, 2013 (supervisor)
- Times Higher Education - One of ten young leading academics in the UK who are making a very significant contribution to their disciplines, 2008
- First Prize of IEEE Asia-Pacific Postgraduate Paper Contest, 2002
- Motorola Book Prize on Robotics and Automation, 2000
- Singapore NTU Dean's List Awards, 2000, 1999, 1998, 1997
Postgraduate research supervision
- Steven Kay (10/2020-present): Computation-aware SLAM for planetary exploration (supported by GMV-UK)
- Thomas Barbier (01/2019-present): Sensor fusion and GNC for active space debris removal (funded by ESA-ECSAT)
- Sadra Bolourian (01/2018-present): Data fusion for industrial environment (funded by NDA)
- Robert Skilton (02/2017-present): Reconfigurable autonomy for nuclear energy fusion applications (funded by UKAEA).
Research fellows I am supervising/line managing
- Sam Simaei (07/2021-present): Robotic manipulation and grasping (funded by UKRI/UKSA)
- Dr Duo Zhang (07/2020-present): Robotics for industrial 6th sense (funded by EPSRC)
- Dr Craig Pitcher (05/2019-present): Integrated design and testing for planetary drilling (funded by UKRI/UKSA).
- Dr Arunkumar Rathinam (05/2019-present): Spacecraft dynamics control (funded by UKRI/UKSA).
- Dr Ka Ho (Xavier) Pang (05/2019-present): Numerical modelling and optimization of biomimetic planetary drilling mechanisms (funded by UKRI/UKSA).
- Dr Arthur Bouton (05/2018-present): Planetary rover chassis and mechanism design (funded by UKRI/UKSA)
- Dr Daniel Zhou Hao (04/2018-present): GNC for space robotic systems (funded by UKRI/UKSA).
Completed postgraduate research projects I have supervised
- Dr Pedro Proenca (01/2015-01/2018): Autonomous operation for nuclear alpha plant (funded by Sellafield)
- Dr Conrad Spiteri (04/2012-10/2017): Planetary Robotic Vision Processing for Surface Modelling and Autonomous Navigation
- Pete Blacker (10/2016-2018): Next generation rover GNC (funded by Airbus DS)
- Dr Abadi Chanik (10/2012-09/2016): Spinning S/C Testbed based on ABT (funded by MARA)
- Dr Guy Burroughes (10/2012-12/2016): Reconfigurable Autonomy (partly funded by SSC)
- Dr Craig Pitcher (07/2013-12/2016): Wasp or DRD drill for planetary sampling (funded by OHB)
- Dr Juntian Si (07/2012-12/2016): Planetary Penetrator Attitude Control (funded by CSC)
- Dr Abhinav Bajpai (01/2012-12/2016): Multi-Rover Localization and Navigation (funded by EU FP7 FASTER)
- Raveesh Kandiyil (04/2011-02/2014): Autonomous Planning and Scheduling of Multi-platform Space Mission (funded by EU FP7 FASTER)
- Dr Juan Manuel Delfa (04/2009-07/2015): Planetary Rover Autonomous Operations (funded by ESA/ESOC NPI, collaborative PhD with TUD)
- Dr Robin Raus (10/2009-09/2012): Single-Actuator Attitude Control of Prolate Spinners (funded by EADS Astrium)
- Karin Shala (10/2008-09/2012): Planetary Rover Localization & Mapping (funded by EU FP7 ProVisG)
- Dr Thibault Gouache (10/2008-09/2011): Planetary Drilling Robot & its Autonomous Operation (funded by ESA/ESTEC NPI)
- Alan Wild (10/2007-2009): Sensing & Autonomous Navigation for Planetary Pin-point Landing (funded by RICS)
- Simon Ye Chen (07/2008-12/2010): Autonomous Operation of Space Robotic Agents (funded by SSC)
Research fellows I have supervised/line managed
- Dr Nikos Mavrakis (10/2018-07/2021): Orbital robotic grasping and manipulation (funded by UKRI/UKSA)
- Dr Mohamed Alkalla (05/2018-04/2021): Planetary “wasp drill” (funded by UKRI/UKSA)
- Dr. Mohamed Abdelwahab (01/2018-07/2020): Industrial 6th sense (funded by EPSRC)
- Dr. Pedro Proenca (04/2018-06/2020): 3D sensing & perception for space robotic system (funded by UKRI/UKSA)
- Dr. Angadh Nanjangud (09/2017-08/2018): On-orbit operation based on AI robotics (funded by space industry and EPSRC)
- Dr. Ivan Vitanov (06/2017-09/2018): Autonomous Nuclear Waste Decommissioning (funded by Sellafield)
- Dr. Miranda Bradshaw (01/2016-10/2018): Space Metrology for Proba3 and LunaResource Missions (funded by KTP)
- Dr. Yuanchang Liu (05/2017-04/2018): LIDAR-Camera Fusion for Planetary Robotic Navigation (funded by UKSA)
- Dr. Affan Shaukat (09/2012-02/2017): LIDAR-Camera Fusion for Planetary Robotic Navigation (funded by UKSA); High Precision GNC for Planetary Robotic Arm (funded by UKSA); Reconfigurable Autonomy (funded by EPSRC); Next Generation Rover GNC (funded by EADS Astrium UK); Multi-agent Social Models for Engineering Applications (funded by MILES)
- Dr. Wissam Albukhanajer (11/2014-05/2017): Agriculture mobile robots (funded by STFC)
- Dr. Brian Yeomans (07/2014-07/2015): Surrey Rover Autonomous Software and Hardware Testbed (SMART)
- Dr. Said Al-Milli (01/2011-06/2014): Surrey Rover Autonomous Software and Hardware Testbed (SMART); Next Generation Rover GNC (funded by EADS Astrium UK); EU FP7 ProVisG Planetary Robotic Vision Processing; EU FP7 FASTER Forward Acquisition of Soil and Terrain data for Exploration Rover
- Dr. Yunhua Wu (01/2010-10/2012): Single-Actuator Slew for Spinning Spacecraft (funded by EADS Astrium)
- Dr. Tom Frame (01/2011-07/2012): Planetary Drilling using DRD (funded by EU)
- Dr. Renato Samperio (01/2010-04/2011): Surrey Rover Autonomous Software and Hardware Testbed (SMART)
- Dr. Minh-Tri Pham (09/2009-10/2010): EU FP7 ProVisG Planetary Robotic Vision Processing
- Dr. Dario Sancho (09/2008-06/2009): Autonomous Terrain Classification (funded by SSC).
Visiting staff and students I have supervised/line managed
- Wei Huang (01/2015-06/2015): Spacecraft onboard image processing (funded by CAST)
- Professor Jinguo Liu (01/2014-12/2014, 2016): Reconfigurable Nano-spacecraft Technology for Space Station (funded by CAS, RAEng)
- Dr Akihiko Honda (from TokyoTech, 07/2013-present): Planetary Rover SLAM
- Dr Ji Sun (10/2012-07/2013): Multi-Satellite Ground Station (funded by CAST)
- Xiongwen He (10/2012-05/2013): Multi-Satellite Ground Station (funded by CAST)
- Professor Shijie Zhang (01/2012-12/2012): Autonomous Operation of Multiple Space Vehicles (funded by RAEng)
- Dr Jiawei Lin (01/2012-06/2012): Vision-based Attitude Determination for Airbearing Table (funded by CAST)
- Dr Chuanfeng Wei (07/2007-07/2008): Planetary Penetrator & Penetrometers (funded by CSC).
- Dr Xiaoyan Chen (from BUAA, 10/2007-06/2009): High-Performance Micro-Rover System Design (funded by CSC)
- Dr Mengping Zhu (from BUAA, 10/2007-05/2009): Altitude Control of Lunar Penetrators (funded by CSC).
Professional staff I have line managed
Project management, administration and partnership support staff.
Courses I teach on
- Project supervision (for MSc and UG, since 2007)
- Personal tutor (for MSc and UG, since 2008)
- ENG3162 Group Design Project (for UG students, since 2020)
- EEE2043 Space Engineering and Mission Design (for UG students, 2007-2018)
- EEEM029 Space Robotics & Autonomy (for MSc/MEng students, 2007-2019)
- EEE3005 Control Engineering (for UG, 2015-2016)
- EEE2036/2037 Lab, Design and Professional Studies (for UG, 2008-2014)
- Bespoke short course on Intelligent Space Systems and Operations (for industry and academic professionals, since 2012)
- Invited lecture for summer schools (for UG/PG) and short courses (for industrial professionals, since 2009):
- COSPAR Summer School on Lunar and Planetary Surface Science, Harbin, 6-19 September 2009
- National Graduates Summer School on Space Technology, Changsha, 18-31 July 2011
- EU FP7 Planetary Vision Summer School, Berlin, 12-16 Sept 2011
- NASG Annual Bespoke Courses on Geospatial Engineering, Nottingham, 2014, 2015, 2016
- Guest Lecture on Space MSc Course, International Space University, Strasbourg, Feb 2019
- International Summer School on Space and Intelligent Systems, online, July 2021
Terrain traversability analysis plays a major role in ensuring safe robotic navigation in unstructured environments. However, real-time constraints frequently limit the accuracy of online tests especially in scenarios where realistic robot-terrain interactions are complex to model. In this context, we propose a deep learning framework trained in an end-to-end fashion from elevation maps and trajectories to estimate the occurrence of failure events. The network is first trained and tested in simulation over synthetic maps generated by the OpenSimplex algorithm. The prediction performance of the Deep Learning framework is illustrated by being able to retain over 94% recall of the original simulator at 30% of the computational time. Finally, the network is transferred and tested on real elevation maps collected by the SEEKER consortium during the Martian rover test trial in the Atacama desert in Chile. We show that transferring and fine-tuning of an application-independent pre-trained model retains better performance than training uniquely on scarcely available real data.
Driving energy consumption plays a major role in the navigation of mobile robots in challenging environments, especially if they are left to operate unattended under limited on-board power. This paper reports on first results of an energyaware path planner, which can provide estimates of the driving energy consumption and energy recovery of a robot traversing complex uneven terrains. Energy is estimated over trajectories making use of a self-supervised learning approach, in which the robot autonomously learns how to correlate perceived terrain point clouds to energy consumption and recovery. A novel feature of the method is the use of 1D convolutional neural network to analyse the terrain sequentially in the same temporal order as it would be experienced by the robot when moving. The performance of the proposed approach is assessed in simulation over several digital terrain models collected from real natural scenarios, and is compared with a heuristic inclination-based energy model. We show evidence of the benefit of our method to increase the overall prediction r2 score by 66:8% and to reduce the driving energy consumption over planned paths by 5:5%.
The low-cost and short-lead time of small satellites has led to their use in science-based missions, earth observation, and interplanetary missions. Today, they are also key instruments in orchestrating technological demonstrations for on-orbit operations (O3) such as inspection and spacecraft servicing with planned roles in active debris removal and on-orbit assembly. This paper provides an overview of the robotics and autonomous systems (RASs) technologies that enable robotic O3 on smallsat platforms. Major RAS topics such as sensing & perception, guidance, navigation & control (GN&C) microgravity mobility and mobile manipulation, and autonomy are discussed from the perspective of relevant past and planned missions.
© 2015 COSPAR. The dual-reciprocating drill (DRD) is a biologically-inspired concept which has shown promise in planetary environments, requiring a lower overhead force than traditional rotary drilling techniques. By using two reciprocating backwards-facing teethed halves to grip the surrounding substrate, it generates a traction force that reduces the required overhead penetration force. Research into DRD has focused on the effects of operational and substrate parameters on performance compared to static penetration, with minimal study of the geometrical parameters which define the drill head. This paper presents the exploration of the effects of drill head design on drilling depth and power consumption. Sixteen variations of the original design were tested in planetary regolith simulants up to depths of 800. mm. The experiments showed relationships between final depth, total drill radius and cone shape, though the teeth design had a negligible effect on performance. These results can be used alongside the previous research to optimise the future design and operation of the DRD. Drill stem bending was seen to cause an increase in drilling speed and depth, leading to the exploration of the mechanics of diagonal drilling. This resulted in the proposal of a fully-integrated system prototype that incorporates both reciprocating and lateral motion mechanisms.
As icy regolith is believed to exist in the subsurface of permanently shadowed areas near the lunar south pole, there is a growing interest in obtaining samples from these polar regions. To qualify for spaceflight, sampling instruments must demonstrate their ability to operate in the expected environment. However, there is currently no quantitative data detailing the extent and distribution of ice in polar regolith. While work has been done to determine the effects of water ice content in simulants such as JSC-1A, to date there has been no investigation into the properties of icy simulants of the regolith believed to be found at lunar polar regions. A series of experiments has therefore been conducted to determine the properties of icy NU-LHT-2M lunar highland simulant, an approximation of lunar polar regolith, at varying degrees of saturation. A number of procedures for preparing the simulant were tested, with the aim of defining a standardised technique for the creation of icy simulants with controlled water contents. Saturation of the highland simulant was found to occur at a water mass content between 13% and 17%, while cone penetration tests demonstrated that a significant increase in penetration resistance occurs at 5 ± 1%. Uniaxial compression tests showed an increase in regolith strength with water mass and density, which slows down as the saturation level is reached. The results presented here demonstrate the first characterisation of the properties of icy lunar polar regolith simulants, which can be expanded upon to further the understanding of its properties for use in future instrumentation testing.
Active depth cameras suffer from several limitations, which cause incomplete and noisy depth maps, and may consequently affect the performance of RGB-D Odometry. To address this issue, this paper presents a visual odometry method based on point and line features that leverages both measurements from a depth sensor and depth estimates from camera motion. Depth estimates are generated continuously by a probabilistic depth estimation framework for both types of features to compensate for the lack of depth measurements and inaccurate feature depth associations. The framework models explicitly the uncertainty of triangulating depth from both point and line observations to validate and obtain precise estimates. Furthermore, depth measurements are exploited by propagating them through a depth map registration module and using a frame-to-frame motion estimation method that considers 3D-to-2D and 2D-to-3D reprojection errors, independently. Results on RGB-D sequences captured on large indoor and outdoor scenes, where depth sensor limitations are critical, show that the combination of depth measurements and estimates through our approach is able to overcome the absence and inaccuracy of depth measurements.
The Powdered Sample Dosing and Distribution System (PSDDS) of the ExoMars rover will be required to handle and contain samples of Mars regolith for long periods of time. Cementation of the regolith, caused by water and salts in the soil, results in clumpy material and a duricrust layer forming on the surface. It is therefore possible that material residing in the sampling system may cement, and could potentially hinder its operation. There has yet to be an investigation into the formation of duricrusts under simulated Martian conditions, or how this may affect the performance of sample handling mechanisms. Therefore experiments have been performed to create a duricrust and to explore the cementation of Mars analogues, before performing a series of tests on a qualification model of the PSDDS under simulated Martian conditions.It was possible to create a consolidated crust of cemented material several millimetres deep, with the material below remaining powder-like. It was seen that due to the very low permeability of the Montmorillonite component material, diffusion of water through the material was quickly blocked, resulting in a sample with an inhomogeneous water content. Additionally, samples with a water mass content of 10% or higher would cement into a single solid piece. Finally, tests with the PSDDS revealed that samples with a water mass content of just 5% created small clumps with significant internal cohesion, blocking the sample funnels and preventing transportation of the material. These experiments have highlighted that the cementation of regolith in Martian conditions must be taken into consideration in the design of sample handling instruments.
As we explore our solar system and other extraterrestrial bodies, the subsurface plays a vital role in allowing us to peer back into the history of a particular body, looking for life or signs that it may have been habitable. This can be achieved by using a form of drill or penetrator, although traditional technologies require large masses to produce an overhead force (OHF) that pushes the drill into the subsurface. Dual reciprocating drilling (DRD) is a new biologically inspired technology based on the wood wasp ovipositor. It consists of two reciprocating backward-facing teethed halves that generate a drilling force that reduces the required overhead penetration force and mass requirements. The Surrey Space Centre (SSC) has overseen the design, development, and testing of a proof-of-concept model with funding from European Space Agency. The system is now evolving to include a drive mechanism within the drill head and bays for scientific instrumentation.
This contribution introduces the development of an intelligent monitoring and control framework for chemical processes, integrating the advantages of Industry 4.0 technologies, cooperative control and fault detection via wireless sensor networks. Using information on the process’ structure and behaviour, equipment information, and expert knowledge, the system is able to detect faults. The integration with the monitoring system facilitates the detection and optimises the controller’s actions. The results indicate that the proposed approach achieves high fault detection accuracy based on plant measurements, while the cooperative controllers improve the control of the process.
This paper proposes a novel object detection method based on the visual saliency model in order to reliably detect objects such as rocks from single monocular planetary images. The algorithm takes advantage of the relatively homogeneous and distinct albedos present in planetary environments such as Mars or the Moon to extract a Digital Terrain Model of a scene using photoclinometry. The Digital Terrain Model is then incorporated into a bottom-up visual saliency algorithm to augment objects that protrude out of the ground. This Structure Augmented Monocular Saliency algorithm (SAMS) improves the accuracy and reliability of detecting objects in a planetary environment with no training requirements, greater robustness and lower computational complexity than 3D saliency models. Comprehensive analysis of the proposed method is performed using three challenging benchmark datasets. The results show that the Structure Augmented Monocular Saliency (SAMS) algorithm performs better than against commonly used visual saliency models on the same datasets
Recently, the fifth-generation (5G) cellular system has been standardised. As opposed to legacy cellular systems geared towards broadband services, the 5G system identifies key use cases for ultra-reliable and low latency communications (URLLC) and massive machine-type communications (mMTC). These intrinsic 5G capabilities enable promising sensor-based vertical applications and services such as industrial process automation. The latter includes autonomous fault detection and prediction, optimised operations and proactive control. Such applications enable equipping industrial plants with a sixth sense (6S) for optimised operations and fault avoidance. In this direction, we introduce an inter-disciplinary approach integrating wireless sensor networks with machine learningenabled industrial plants to build a step towards developing this 6S technology. We develop a modular-based system that can be adapted to the vertical-specific elements. Without loss of generalisation, exemplary use cases are developed and presented including a fault detection/prediction scheme, and a sensor density-based boundary between orthogonal and non-orthogonal transmissions. The proposed schemes and modelling approach are implemented in a real chemical plant for testing purposes, and a high fault detection and prediction accuracy is achieved coupled with optimised sensor density analysis.
It is widely acknowledged that the next significant challenge in planetary exploration is to be able to drill deeply (two meters seems the most scientifically valuable and the most technologically reasonable) into the surface of solar system bodies for chemical or physical data. Major limitation of using conventional rotary drills in low gravity environments (such as Mars, asteroids, comet, etc) is the need for high axial force, which suffers from big overhead mass, buckling problem, and power hungriness. Though drills using percussive motion may operate in low mass and power, the drilling rate is generally slow. Drawing inspiration from nature for a lightweight and energy efficient solution, we propose a novel drilling method based on the working mechanism of wood wasp ovipositors. The bio-inspired drill requires no reactive external force by applying two-valve-reciprocating motion. The proposed bio-inspired system indicates enhanced utility that is critical for space missions where premium is placed on mass, volume and power. Biological systems are similarly constrained making biomimetic technology uniquely suited and advantageous as a model of miniaturized systems. As a result of the European Space Agency (ESA) project on bionics and space system design [Ellery, 2005], this paper presents a conceptual design of the bio-inspired drill. Lab-based experiments have shown that the two-valve-reciprocating drilling method is feasible and has potential of improving drill efficiency without any additional overhead force or mass.
Robotics and autonomous systems have been instrumental to space exploration by enabling scientific breakthroughs and by fulfilling human curiosity and ambition to conquer new worlds. We provide an overview of space robotics as a rapidly emerging field, covering basic concepts, definitions, historical context, and evolution. We further present a technical road map of the field for the coming decades, taking into account major challenges and priorities recognized by the international space community. Space robotics represents several key enablers to a wide range of future robotic and crewed space missions as well as opportunities for knowledge and technology transfer to many terrestrial sectors. In the greater humanitarian context, space robotics inspires both current and future generations to exploration and critical study of science, technology, engineering, and mathematics.
This position paper describes ongoing work at the Universities of Liverpool, Sheffield and Surrey in the UK on developing hybrid agent architectures for controlling autonomous systems, and specifically for ensuring that agent-controlled dynamic reconfiguration is viable. The work outlined here forms part of the Reconfigurable Autonomy research project.
This paper presents a robust Adaptive Fuzzy Neural Controller (AFNC) suitable for trajectory control of robot manipulators. The proposed controller has the following salient features: (1) Self-organizing fuzzy neural structure, i.e. fuzzy control rules can be generated or deleted automatically according to their significence to the control system and the complexity of the mapped system, and no predefined fuzzy rules are required; (2) Online learning, i.e. no prescribed training models are needed for online learning; (3) Fast learning speed, i.e. Generalized Dynamic Fuzzy Neural Network (GD-FNN) algorithm provides an efficient learning method. Moreover, weights of the AFNC are modified without using the Back-Propagation (BP) iteration method. Structure and parameters identification of the AFNC are done automatically and simultaneously without partitioning the input space and selecting initial parameters a priori; (4) Fast convergence of tracking error, i.e. manipulator joints can track the desired trajectory very quickly; (5) Adaptive control, i.e. structure and parameters of the AFNC can be self-adaptive in the presence of disturbances to maintain high control performance; (6) Robust control, i.e. asymptotic stability of the control system is established using Lyapunov theorem. Computer simulation studies were carried out and comparison of simulation results with some existing controllers demonstrate the flexibility, adaptability and good tracking performance of the proposed controller.
This paper investigates state-of-the-art approaches for object detection and tracking employing models that can efficiently detect objects (specifically 'rock’ on planet surfaces) in the visual scene in terms of semantic descriptions. Two models (i.e., “visual saliency” and “blob (shape-based) detection”) are presented here specifically focused towards future planetary exploration rovers. We believe that these two object detection techniques will abate some of the algorithmic limitations of existing methods with no training requirements, lower computational complexity and greater robustness towards visual tracking applications over long-distance planetary terrains. Comprehensive (quantitative) experimental analysis of the proposed techniques performed using three challenging benchmark datasets (i.e., from PANGU, RAL Space SEEKER and SSC lab-based test-bed) will be presented in this paper.
The paper aims to address the challenge of performing precise spin-axis reorientation maneuver for prolate spacecraft (e.g. kinetic planetary penetrators) spinning about its minimal inertia axis using a single body fixed attitude control thruster, which takes into account constraints of dynamics, phase boundary and slew time, etc. Spin stabilization is an attractive way for providing attitude pointing stability to a spacecraft due to its simplicity and ability to reject against various disturbances, such as gravity gradient disturbance torque and liquid sloshing disturbance torque. This is deemed applicable to various missions involving upper stages, multiple unit cubesats, and kinetic impactors such as for MoonLITE and NEOShield projects. Furthermore, for spinners using one attitude control thruster that is perpendicular to the spin axis is theoretically feasible and advantageous in terms of simplicity and redundancy in comparison to 3-axis stabilization control. Spin Sync slew algorithm is recently developed for the single thruster attitude control of prolate spinners. It possesses similar characteristic as Rhumb Line slew, but can be implemented to overcome the inherent singularity of the Rhumb Line slew and sun sensor failure. Both Spin Sync and Rhumb Line slews still have issues with residual nutation angle and potential divergence of the angular momentum trajectory. In this paper, a geometric method is proposed to estimate and compensate the angular momentum vector divergence. In addition, the paper presents solutions to achieve precise attitude control using spin sync slew. This is a difficult problem due to nonlinear and nonconvex attitude dynamics and constraints and is hence treated as a nonlinear multi-phase optimal control problem with constraints related to initial and terminal state, control torque magnitude, attitude dynamics, and slew time. Here, the optimization is achieved by direct transcription using Gauss pseudo-spectral method, in which the varying boundary problem is converted to a fixed boundary problem by varying optimization parameters. Computer simulations and results are provided to demonstrate the proposed approach. The optimal control achieved is also verified using engineering software simulator of 'Attitude Control Simulator for Spinning Spacecraft with Single Thruster'.
As a part of the Aurora programme for Mars exploration, funded by the United Kingdom Space Agency (UKSA) and European Space Agency (ESA), the UK contributes to the Exobiology on Mars (ExoMars) rover science and engineering programme, with a scheduled launch in 2018; Hence, our Panoramic Camera (PanCam)  research and development (R&D) is timely. PanCam consists of two stereo Wide Angle Cameras (WAC) and one High Resolution Camera (HRC). While the development is still ongoing, we used funding awarded by the University College London (UCL) Graduate School to conduct investigations in the Himalayas and at Mount Everest Base Camp (EBC), according to the ExoMars rover Reference Surface Mission (RSM). The investigations included capturing stereo and high resolution images using stereo WAC emulators and HRC emulator at altitudes 3490 m, 5150 m and above. Images from different WAC filters, and color images from HRC were acquired at various Pan and Tilt Unit (PTU) mast positions. Our investigation results show significant reduction in data volume with minimum loss in image quality. Furthermore, we introduce a novel autonomous and computational intelligent system called Mission-Specific Data Processor (MSDP) for the rover. It includes Pan-Cam, Visual Data Fusion (VDF), Learning-enabled Object Detection (LOD), Self-Learning Agent (SLA) , and Environment Model Library (EML) as part of the rover's computational intelligence . © 2013 IEEE.
This paper describes a computer-simulated virtual reality environment for planetary rover operation and testing. The proposed 3D Virtual Rover Operation Simulator (VROS) consists of rover model, perception of the planetary surface, and rover-terrain contact model, which provides a simulation platform to test and validate different rover chassis design, navigation and locomotion algorithms, and to support rover operation. Lab-based experiments have been carried out and results can demonstrate various functions of VROS and its performance.
This work investigates the potential use of direct ultrasonic vibration as an aid to penetration of granular material. Compared with non-ultrasonic penetration, required forces have been observed to reduce by an order of magnitude. Similarly, total consumed power can be reduced by up to 27%, depending on the substrate and ultrasonic amplitude used. Tests were also carried out in high-gravity conditions, displaying a trend that suggests these benefits could be leveraged in lower gravity regimes.
Current techniques for the exploration of planetary surfaces are slow, and involve frequent human intervention. Rapid growth in complexity of future missions requires the development of ambitious technologies that may allow remotely deployable vehicles to carry out a majority of their tasks autonomously. Mapping and localisation is a key area of planetary exploration that can benefit from an increased level of autonomy, for instance in upcoming missions such as ExoMars and the ESA sample return proposal FASTER. Simultaneous Localisation And Mapping (SLAM) is a technique developed for terrestrial uses allow autonomous vehicles to calculate their position in an unknown environment, whilst also creating a map. This technique can be transferred to a planetary platform in order to allow the rover to better traverse through its environment without human intervention. While several techniques existed for implementing SLAM in a terrestrial environment, the use of SLAM for planetary exploration has not been explored in depth. The use of LIDAR, commonly used in terrestrial SLAM implementations, is a complex solution for use in space missions, and has yet to be robustly proven. Therefore, another means of observing the environment, a key part of the SLAM algorithm, is required. Monocular cameras together with vision processing algorithms present a simple scenario well suited to the scenario. The work presented in this paper comprises the design and implementation of a fully end-to-end, modular planetary SLAM system. The system takes data from the Planetary and Asteroid Natural scene Generation Utility, and using vision based algorithms passes observation data to one of three SLAM filters, the Extended Kalman Filter, the Extended Information Filter and FastSLAM. The results show that these techniques and filters are well suited to the planetary environment and provide a route towards extending rover autonomy. ©2013 by the International Astronautical Federation. All rights reserved.
Emplacement of four or more kinetic penetrators geographically distributed over the lunar surface can enable a broad range of scientific exploration objectives of high priority and provide significant synergy with planned orbital missions. Whilst past landed missions achieved a great deal, they have not included a far-side lander, or investigation of the lunar interior apart from a very small area on the near side. Though the LCROSS mission detected water from a permanently shadowed polar crater, there remains in-situ confirmation, knowledge of concentration levels, and detailed identification of potential organic chemistry of astrobiology interest. The planned investigations will also address issues relating to the origin and evolution of the Earth–Moon system and other Solar System planetary bodies. Manned missions would be enhanced with use of water as a potential in-situ resource; knowledge of potential risks from damaging surface Moonquakes, and exploitation of lunar regolith for radiation shielding. LunarNet is an evolution of the 2007 LunarEX proposal to ESA (European Space Agency) which draws on recent significant advances in mission definition and feasibility. In particular, the successful Pendine full-scale impact trials have proved impact survivability for many of the key technology items, and a penetrator system study has greatly improved
© Springer International Publishing Switzerland 2014.Search and rescue robots would benefit from versatile locomotion ability and hence cope with varying environments. Robot snakes, with hyperredundant body and unique gaits, offer a promising solution to search and rescue applications. This paper presents a portable design of robot snakes that can be controlled from commercial mobile devices like the smartphones. The control results are validated and demonstrated using hardware prototypes.
By measuring the centroid of a beam on a detector, one can track the movement of that beam across the detector. By tracking this movement, one can track the object encompassing the detector, for example, a spacecraft. A variety of system-specific performance inhibitors can make this a challenge, requiring a robust calibration method. The goal of this investigation is to model the true beam position of the instrument in terms of the measured beam position. For this, a mathematical model is created that interpolates and corrects the measured beam position using precollected position data—a "calibration model." The real-world scenario for this investigation is the flight-representative model of the fine lateral and longitudinal sensor (FLLS) instrument, built by Neptec Design Group and Neptec UK for the European Space Agency mission PROBA-3. Performance inhibitors for FLLS are cropping of the beam, imperfect optics, and a varying distance the beam has traveled (up to 250 m). Using bivariate spline interpolation for the FLLS calibration model gives the best performance, achieving a measurement accuracy well within the mission requirement of
There is evidence that water-ice exists on a number of bodies in the solar system. As ice deposits may contain biomarkers that indicate the presence of life, or can be used as a consumable resource for future missions, confirming these observations with in-situ measurements is of great interest. Missions aiming to do this must consider how the presence of water-ice in regolith affects both the regolith’s properties and the performance of the instruments that interact with it. The properties of icy lunar and Martian regolith simulants in preparation for currently planned missions are examined in this chapter. These results can be used in future instrumentation testing and missions designed to explore other icy bodies in the solar system. The testing of icy lunar regolith simulants is summarised, before focusing on experiments demonstrating the change in properties of frozen NU-LHT-2M, a simulant of the highlands regolith found at the lunar poles, as water is added. Further tests showed a critical point of 5 ± 1% water mass content where the penetration resistance significantly increases. The addition of water to Martian regolith simulants was also examined, with the presence of salts resulting in the formation of cemented crusts under simulated Martian conditions. Additional tests with the ExoMars PSDDS demonstrated how increased internal cohesion caused by the water resulted in the failure of the instrument.
This contribution introduces a framework for the fault detection and healing of chemical processes over wireless sensor networks. The approach considers the development of a hybrid system which consists of a fault detection method based on machine learning, a wireless communication model and an ontology-based multi-agent system with a cooperative control for the process monitoring.
Astrophysicists demand larger (mirror diameter > 10m) space optical telescopes to investigate more distant events that happened during the very early period of the universe, for example formations of the earliest stars. The deployable telescope design like James Webb Space Telescope that has a 6.5m diameter primary mirror has already reached the capacity limits of the existing launch vehicles. Therefore, the space industry has been considering using robotic technologies to build future optical reflecting three-mirror structured space telescopes in orbit from smaller components. One of the design paradigms is to use a high-DOF manipulator on a free-flying platform to build the optical telescope in orbit. This approach requires high precision and accuracy in the robotic manipulation GNC system that has several challenges yet to be addressed: 1. Orbital environmental parameters that affect sensing and perception; 2. Limitations in robotic hardware, trajectory planning algorithms and controllers. To investigate these problems for in-orbit manipulation, the UK national hub on future AI and robotics for space (FAIR-SPACE) at the Surrey Space Centre (SSC) has been developing a ground-based hardware-in-the-loop (HIL) robotic demonstrator to simulate in-orbit manipulation. The key elements of the demonstrator are two 6-DOF manipulators and a re-configurable sensor system. One of the manipulators with a > 3-DOF gripping mechanism represents the assembly manipulator on a spacecraft whose orbital dynamics, kinematics, and environmental disturbances and uncertainties are propagated in a computer. The other 6-DOF manipulator with a torque/force sensor is used as a gravity offoad mechanism to carry the space telescope mirror segment. The relative motions between the service/manipulation arm and the mirror segment are computed and then executed by the second arm. The sensor system provides visual feedback of the end-effector and uses computer vision and AI to estimate the pose and position of the mirror segment respectively. The demonstrator aims to verify and validate the manipulator assembly approach for future large space optical telescopes against ground truth and benchmarks. This paper explains the motivation behind developing this testbed and introduces the current hardware setup of the testbed and its key features.
In many types of space mission there is a constant desire for larger and larger instrument apertures, primarily for the purposes of increased resolution or sensitivity. In the Radio Frequency domain, this is currently addressed by antennas that unfold or deploy on-orbit. However, in the optical and infrared domains, this is a significantly more challenging problem, and has up to now either been addressed by simply having large monolithic mirrors (which are fundamentally limited by the volume and mass lifting capacity of any launch vehicle) or by complex ‘semi-folding’ designs such as the James Webb Space Telescope. An alternative is to consider a fractionated instrument which is launched as a collection of individual smaller elements which are then assembled (or self-assemble) once in space, to form a much larger overall instrument. SSTL has been performing early concept assessment work on such systems for high resolution science observations from high orbits (potentially also for persistent surveillance of Earth). A point design of a 25 m sparse aperture (annular ring) telescope is presented. Key characteristics of 1) multiple small elements launched separately and 2) on-orbit assembly to form a larger instrument are included in the architecture. However, on-orbit assembly brings its own challenges in terms of guidance navigation and control, robotics, docking mechanisms, system control and data handling, optical alignment and stability, and many other elements. The number and type of launchers used, and the technologies and systems used heavily affect the outcome and general cost of the telescope. The paper describes one of the fractionated architecture concepts currently being studied by SSTL, including the key technologies and operational concepts that may be possible in the future.
Returning to the Moon has been advocated by a number of planetary scientists in order to answer several key scientific questions. The UK has an active lunar science community keen to support (robotic) lunar exploration. However, for several years, these interests have been eclipsed by the drive to Mars. Recently there is a renewed global interest in the Moon, demonstrated by the Vision for Space Exploration in the USA, the evolving Global Exploration Partnership, and new lunar missions from Europe, Japan, China and India. The ESA Aurora programme may also broaden its focus to embrace the Moon as well as Mars - realising that many of the major technical challenges that are faced by Mars missions could be de-risked by relatively inexpensive and timely lunar precursors. Surrey Satellite Technology Ltd. (SSTL) and Surrey Space Centre (SSC) have been preparing a 'smallsat' approach to achieving a low-cost lunar mission for more than a decade - including various activities, such as Phase B study of LunarSat funded by ESA and a current hardware contribution to the Chandrayaan-1 mission. With the recent successes in GIOVE-A, TOPSAT & BEIJING-1, alongside participation in Aurora & Chandrayaan-1, Surrey has developed capabilities for providing affordable engineering solutions to space exploration. In 2006, SSTL/SSC was funded by the UK Particle Physics and Astronomy Research Council (PPARC) (now included within the UK Science & Technology Facilities Council) to undertake a study on low-cost lunar mission concepts that could address key scientific questions. This paper presents some major results from this study (Phipps and Gao, 2006) and provides preliminary definitions of two down-selected mission proposals. Copyright IAF/IAA. All rights reserved.
©, 2015, Chinese Academy of Sciences. All right reserved.Marvi et al (Science, 2014, vol.346, p.224) concluded a sidewinder rattlesnake increases the body contact length with the sand when granular incline angle increases. They also claimed the same principle should work on robotic snake too. We have evidence to prove that this conclusion is only partial in describing the snake body-sand interaction. There should be three phases that fully represent the snake locomotion behaviors during ascent of sandy slopes, namely lifting, descending, and ceasing. The snake body-sand interaction during the descending and ceasing phases helps with the climbing while such interaction during the lifting phase in fact contributes resistance.
The upcoming lunar lander missions, for example Chang’e 2 from CNSA and several mission proposals and studies currently under consideration at NASA (e.g. Neal et al., ROSES 2006 Proposal to NASA, 2006), ESA (e.g. Hufenbach, European Workshop on Lunar Landers, ESTEC, Noordwijk, The Netherlands, 2005; Foing, EPSC Abstracts, vol 2, EPSC2007-A-00422, European Planetary Science Congress, Potsdam, Germany, 2007) and JAXA, Japan (Matsumoto et al., Acta Astronautica, 59:68–76, 2006) offer new possibilities to measure the thermal properties of the lunar regolith and to determine the global lunar heat flow more accurately than it is hitherto known. Both properties are of high importance for the understanding of the lunar structure and the evolution of the Moon–Earth system. In this paper we present some work on new thermal sensors to be used for in situ investigations of the lunar soil in combination with novel drilling techniques applicable for the lunar regolith. Such systems may preferably be mounted on mobile stations like the lunar rover currently built for the Chinese Chang’e 2 mission. A general description of a presently tested prototype of the lunar rover is given and mounting possibilities for a drilling system and thermal sensors are shown. Then we discuss some options for thermal sensors and drills and how they could be combined into one compact instrument. Subsequently a tube-like sensor suitable for measuring the thermal conductivity of the material surrounding a borehole is described in more detail. Finally the performance of such a tube-shaped sensor when applied in a lunar borehole is investigated by thermal modelling and compared with the behaviour of a more conventional needle-shaped sensor.
The ground verification of a spacecraft control algorithm is commonly done via air bearing facility. Air bearing testbeds are frequently developed for testing a three-axis stabilized spacecraft control algorithm but hardly for a spin-stabilized spacecraft. A modular testbed for testing a spinning spacecraft has been developed at Surrey Space Centre initially for the real-time verification of a prolate spinner slew control algorithm. This testbed is made from commercial off-the-shelf components with a modular system design approach through rapid control prototyping using Matlab xPC Target and is extendable to other rapid control prototyping techniques. It is equipped with a novel low-cost monocular vision system for attitude determination with accuracy of 0.06 deg and angular velocity accuracy of 0.15 deg/s0.15 deg/s. For the current specification, a cold-gas propulsion system is fixed to the testbed with a two-degree-of-freedom thruster set that can deliver up to 0.25 N of thrust and an air bearing capability that gives three degrees of freedom with a maximum tilt angle of 30 deg. In this paper, the testbed implementation is described, and the test platform is verified.
Y. Gao et al. proved the feasibility of designing a woodwasp (Sirex Noctilio) inspired drill for Earth and extraterrestrial drilling and boring activities . But before an optimised dual reciprocating drill design can be proposed, it is necessary to better understand the driving factors and the important parameters that influence this mechanism’s performance and, power and force requirements. Indeed the insect’s ovipositor is "optimised", through natural selection, for wood; but the dual reciprocating drill will bore into much different substrates. Here, the numerous parameters that could influence the studied mechanism’s performance are identified and the test bench to
This book contains an edited collection of eighteen contributions on soft and hard computing techniques and their applications to autonomous robotic systems.
The nonlinear autoregressive moving average with exogenous inputs (NARMAX) model provides a powerful representation for time series analysis, modeling and prediction due to its capability of accommodating the dynamic, complex and nonlinear nature of real-world time series prediction problems. This paper focuses on the modeling and prediction of NARMAX-model-based time series using the fuzzy neural network (FNN) methodology. Both feedforward and recurrent FNNs approaches are proposed. Furthermore, an efficient algorithm for model structure determination and parameter identification with the aim of producing improved predictive performance for NARMAX time-series models is developed. Experiments and comparative studies demonstrate that the proposed FNN approaches can effectively learn complex temporal sequences in an adaptive way and they outperform some well-known existing methods.
Due to ultraviolet flux in the surface layers of most solar bodies, future astrobiological research is increasingly seeking to conduct subsurface penetration and drilling to detect chemical signature for extant or extinct life. To address this issue, we present a micro-penetrator concept (mass < 10 kg) that is suited for extraterrestrial planetary deployment and in situ investigation of chemical and physical properties. The instrumentation in this concept is a bio-inspired drill to access material beneath sterile surface layer for biomarker detection. The proposed drill represents a novel concept of two-valve-reciprocating motion, inspired by the working mechanism of wood wasp ovipositors. It is lightweight (0.5 kg), driven at low power (3 W), and able to drill deep (1-2 m). Tests have shown that the reciprocating drill is feasible and has potential of improving drill efficiency without using any external force. The overall penetration system provides a small, light and energy efficient solution to in situ astrobiological studies, which is crucial for space engineering. Such a micro-penetrator can be used for exploration of terrestrial-type planets or other small bodies of the solar system with the minimum of modifications.
This book collects a number of representative methods on sensory evaluation.
The large success of Mars exploration missions, such as the NASA Mars Exploration Rovers, Pathfinder and Viking I and II, have allowed a widespread access to the top layer of Martian regolith. However, no exploration deeper than the few centimetres allowed by the scoop of Phoenix has been conducted on Mars. The potential discoveries that will follow from access to the Martian sub-surface (for example, the presence or absence of extinct life forms and of resources for future human exploration; a better understanding of Martian and Solar System history) require the development of new tools and a better understanding of their interaction with regolith to increase their performance and reliability. A promising new drilling methodology, dual reciprocating drilling (DRD), was tested in regolith and showed higher penetration than static penetration. DRD is conducted by two half-cone drillheads, with back-ward facing teeth, moved back and forth in opposition one to another (no rotation). To gain a better understanding of the forces acting on each half-drill-bit and the influence of slippage on drilling performance, a mono-block drill-head, with the same shape as the DRD drill-head, was tested in static and alternating penetration in two different regolith simulants. The forces acting on it were measured. These novel experimental observations allowed to revise the penetration model of DRD in regoliths and to illustrate the importance of lateral forces in the drilling process. To complement the experimental campaign and to gain a better insight on the regolith kinematics around the reciprocating drill-head, numerical simulations were developed. The discrete element method was chosen to simulate the complex behaviour of regolith. It was implemented within the commercial software Impetus-AFEA. The advantage of using this platform is its ability to use the power of graphical processing units (GPU) to cope with a very large number of elements within reasonable computation times. These numerical simulations allowed to confirm the importance of the lateral forces in DRD. They are also one of the first DEM simulations with more than one million particles on a single desktop computer and pave the way to highly efficient numerical simulations.
Automated Planning & Scheduling Systems are nowadays applied in a wide range of spacecraft, from satellites to Mars rovers. The planner is responsible for the generation of valid plans that determine the activities to be performed by the spacecraft, given a set of goals and constraints (the problem), and taking into consideration the status of the spacecraft and environment. Therefore, it represents a critical system that needs to be strictly validated and verified. This paper presents a benchmarking tool called RoBen intended to characterize the performance of timeline planning systems. Using a number of metrics and heuristics, RoBen can generate synthetic problems of a given complexity in order to stress planners at different levels. At the same time, we are looking for properties that could help us to determine when a problem is unsolvable. © 2012 by Juan Delfa Victoria, TU Darmstadt, University of Surrey, European Space Agency.
Understanding the lunar near-surface distribution of relevant in-situ resources, such as ilmenite (FeTiO3), and volatiles, such as water/ice, is vital to future sustained manned bases. VMMO is a highly-capable, low-cost 12U Cubesat designed for operation in a lunar frozen orbit. It accomodates the LVMM Lunar Volatile and Mineralogy Mapper and the CLAIRE Compact LunAr Ionising Radiation Environment payloads. LVMM is a multi-wavelength Chemical Lidar using fiber lasers emitting at 532nm and 1560nm, with an optional 1064nm channel, for stand-off mapping of the lunar ice distribution using active laser illumination, with a focus on the permanently-shadowed craters in the lunar south pole. This combination of spectral channels can provide sensitive discrimination of water/ice in various regolith. The fiber-laser technology has heritage in the ongoing Fiber Sensor Demonstrator flying on ESA's Proba-2. LVMM can also be used in a low-power passive mode with an added 280nm UV channel to map the lunar mineralogy and ilmenite distribution during the lunar day using the reflected solar illumination. CLAIRE is designed to provide a highly miniaturized radiation environment and effect monitor. CLAIRE draws on heritage from the MuREM and RM payloads, flown on the UK’s TDS-1 spacecraft. The payload includes PIN-diode sensors to measure ionizing particle fluxes (protons and heavy-ions) and to record the resulting linear energy transfer (LET) energy-deposition spectra. It also includes solid-state RADFET dosimeters to measure accumulated ionizing dose, and dose-rate diode detectors, designed to respond to a Coronal Mass Ejection (CME) or Solar Particle Event (SPE). CLAIRE also includes an electronic component test board, capable of measuring SEEs and TID effects in a selected set of candidate electronics, allowing direct correlations between effects and the real measured environment.
In recent years, there is an increasing demand for orbital robotic missions for various reasons such as life extension of functional satellites, reuse the unique orbital slots and to reduce the risk of orbital collision. In such robotic missions, the satellite’s autonomous navigation capability is a critical component that enables it to perform relative navigation, inspection, and repair with minimal human-in-loop intervention. Pose estimation is an important task within autonomous GNC for spacecraft in orbit. There have been recent, new development of deep learning based pose estimation algorithms in order to meet growing demands of autonomous orbital applications. This paper presents a new keypoint-based framework using Convolutional Neural Network models for pose estimation of known non-cooperative targets in orbit, which is thoroughly compared to existing state-of-the-art algorithms also based on deep learning. Within the proposed pose estimation pipeline, a ResNet-based architecture used for object detection, a Scale-Aware High-Resolution Network (HigherHRNet) used for keypoint regression and PnP-RANSAC for computing the pose. The framework is benchmarked with the SPEED dataset as well as the Soyuz dataset from STAR LAB Orbital Visual Simulator and the results were presented.
This paper describes a novel approach on orbital target capturing of a spent Apogee Kick Motor (AKM), by using robotic finger contact stability analysis similarly to terrestrial robotics. The surface curvature of the nozzle offers a robust candidate contact point. The stability of the grasp is assessed according to the Intrinsic Stiffness Matrix of the grasp and the mass matrix of the target, which are expressed on a common coordinate frame, multiplied, and the minimum eigenvalue of the product serves as a stability criterion. We perform a quantitative analysis to assess the stability over variations of the grasping parameters. We also execute a simulation of a chasing spacecraft equipped with a robot manipulator and gripper, grasping an AKM and pulling it towards its body. The results suggest that the grasp is stable, and the finger displacement from the grasped surface is negligible. The results from this paper can be used to develop autonomous stable grasp planning algorithms for orbital robotics.
This paper presents a new control scheme utilizing fuzzy neural networks for trajectory control of robot manipulators. The adaptive capability of the fuzzy neural controller ensures that high performance can be achieved and maintained under time-varying conditions. This intelligent control scheme consists of two portions. In the first portion, the fuzzy neural networks with dynamic structure, in short DFNNs, are constructed to estimate dynamics of the robot model. The second portion is the fuzzy neural controller, which is built based on model learning and on-line weight adjustment. Computer simulations of a two-link robot manipulator demonstrate the effectiveness and efficiency of the proposed scheme.
In a domain such as space technology, where robustness, mass, volume and power efficiency are key, biological organisms may provide inspiration for new systems with high performance. By using micro-technology processes, designers of space systems may take advantage of the millions of years over which miniaturised mechanisms in plants and animals have been optimised for survival. Space exploration often requires systems equipped with drills, and miniaturised drillers could enable a number of new space operations. Two natural digging systems have been studied as potential miniature space digging systems; the ovipositors of the female locust and of sirex noctilio, a species of woodwasp. Being insectoid systems, the mechanics of their design work on an inherently small scale, though they are also thought to be scalable. Results of preliminary studies, performed during collaboration between the Advanced Concepts Team of ESA, the University of Bath, the University of Surrey, D'appolonia and EADS-Astrium, are presented and discussed. Engineering solutions are proposed and analysed to assess the potential of new bio-inspired miniaturised digging systems for space applications. Copyright © 2006 by ASME.
Radio images of red-shifted 21-cm signals from neutral hydrogen originating from the very early Universe, the so-called Dark Ages before the first stars formed, are impossible to obtain from Earth due to man-made radio frequency interference (RFI) and the opacity of the ionosphere below ∼30 MHz. To efficiently block the RFI, which would otherwise overwhelm the weak cosmological signal, requires a large low-frequency radio array on the far-side of the Moon. Such a lander mission is technically challenging and carries a budget that is currently unlikely to be included in any national or international mission plan. Our goal is to use a constellation of small satellites in lunar orbit to collect pathfinder data to demonstrate the feasibility of using the Moon as a radio-shield, and map out the spatial extent of this RF quiescent zone. The team led by the Hawaii Space Flight Laboratory (HSFL) at the University of Hawaii at Manoa is designing a mission to characterize the spatial extent of the RF quiescence zone on the lunar farside to support future missions to explore the cosmos using radio observatories on the surface. This paper examines the design of this mission starting with a baseline architecture that uses a modified SSTL X50 satellite bus as mothership that carries one or more nanosats to lunar orbit. The mothership will then deploy it/them to form the constellation, as well as act as the communications relay between them and Earth. The initial baseline mission utilizes the standard Super Strypi launch vehicle. Although it is desirable to have a mothership and several nanosats evenly distributed in an equatorial lunar orbit, performance limitations of the standard launch vehicle only permit the mothership with one nanosat in a highly elliptical orbit that would allow measurement of the relevant RF environment continuously for at least a year. The nanosat would crosslink the collected data to the mothership, which will relay the data to Earth as well as act as an RF collecting station itself.
This article presents the design, development, and implementation of a new adaptive fuzzy neural controller (AFNC) suitable for real-time industrial applications. The developed AFNC consists of a combination of a fuzzy neural network (FNN) controller and a supervisory PD controller. The salient features of the AFNC are: (1) dynamic fuzzy neural structure, that is, fuzzy control rules can be generated or deleted automatically; (2) fast on-line learning ability; (3) fast convergence of tracking error; (4) adaptive control; and (5) robust control, where global stability of the system is established using Lyapunov approach. Experimental evaluation conducted on a SEIKO TT-3000 SCARA robot demonstrates that excellent tracking performance can be achieved under time-varying conditions. The proposed controller also outperforms some of the existing adaptive fuzzy and neural controllers in terms of tracking speed and accuracy.
This paper proposes a generic approach towards combining fuzzy logic and ontology-based deliberative reasoning to enable self-reconfigurability within a distributed system architecture. An Ontology-based rational agent uses outputs from a fuzzy inference system (reconfiguration layer) which passively monitors the performance of the lower-level sub-systems (application layer) in order to perform system reconfiguration. A reconfiguration is required to guarantee optimal performance within a complex robotics architecture when anomalous system and environmental changes take place. More importantly, this process of reconfiguration offers greater fault tolerance and reliability in novel scenarios as compared to isolated engineered systems. The current research work will apply the proposed framework to a visual navigation system for autonomous planetary rover missions. This demonstrates the method's success through an increase in system performance following a reconfiguration routine carried out within the application layer between two different types of visual navigation methods. Experimental analysis is carried out using real-world data, concluding that the proposed reconfigurable architecture gives superior performance against standard engineered techniques.
As massive scientific information is trapped inside the geologic formation of planetary bodies, the objectives of most exploration missions mainly involve sampling, in-situ testing and analyzing of the cutting’s formation for seeking any sign of primitive life or resources. This can be accomplished by subsurface exploration by specific drilling techniques which entail challenges that are apparently more complex than drilling on the earth. One of these challenges is the low-gravity that should be compensated by the over-head mass of the drilling system. This excessive mass represents a burden during launching the mission. Therefore, it is necessary to choose an energy efficient and light-weight drilling system capable of reaching high depths. This article focuses on optimizing drill bit geometry (i.e., profiles, cross-sections, and teeth) of the bio-inspired wood-wasp drill for targeting new potential depths into the Martian regolith and reducing its drilling time. Different morphological designs of the drill bit are generated and experimentally tested for their drilling feasibility into fine and coarse-grain Martian regolith. A Comparison between old and new proposed drill bits is presented, based on drilling time, consumed power, and slope of depth-time curve. The proposed designs show a significant reduction of the drilling time between 20% to 56.5% over the old one, while the required over-head mass (OHM) and power to penetrate 760mm depth is only 3kg and 45 watts, respectively. This practical work reveals the necessity of getting customizable drill bits for each single location of the extraterrestrial surfaces even on Moon or Mars based on its unique character which can be categorized as soft and hard formulations.
A key challenge in autonomous planetary surface exploration is the extraction of meaningful information from sensor data, which would allow a good interpretation of the nearby terrain, and a reasonable assessment of more distant areas. In the last decade, the desire to increase the autonomy of unmanned ground vehicles (UGVs), particularly in terms of off-road navigation, has significantly increased the interest in the field of automated terrain classification. Although the field is relatively new, its advances and goals are scattered across different robotic platforms and applications. The objective of this paper is to present a survey of the field from a planetary exploration perspective, bringing together the underlying techniques, existing approaches and relevant applications under a common framework. The aim is to provide a comprehensive overview to the newcomer in the field, and a structured reference for the practitioners.
Planetary monocular simultaneous localization and mapping (PM-SLAM), a modular, monocular SLAM system for use in planetary exploration, is presented. The approach incorporates a biologically inspired visual saliency model (i.e., semantic feature detection) for visual perception in order to improve robustness in the challenging operating environment of planetary exploration. A novel method of generating hybrid-salient features, using point-based descriptors to track the products of the visual saliency models, is introduced. The tracked features are used for rover and map state-estimation using a SLAM filter, resulting in a system suitable for use in long-distance autonomous (micro)rover navigation, and the inherent hardware constraints of planetary rovers. Monocular images are used as an input to the system, as a major motivation is to reduce system complexity and optimize for microrover platforms. This paper sets out the various components of the modular SLAM system and then assesses their comparative performance using simulated data from the Planetary and Asteroid Natural Scene Generation Utility (PANGU), as well as real-world datasets from the West Wittering field trials (performed by the STAR Lab) and the SEEKER field trials in Chile (performed by the European Space Agency). The system as a whole was shown to perform reliably, with the best performance observed using a combination of Hou-saliency and speeded-up robust features (SURF) descriptors with an extended Kalman filter, which performed with higher accuracy than a state-of-the-art, independently optimized visual odometry localization system on a challenging real-world dataset.
Human spaceflight to/on/from the Moon will benefit from exploitation of various in-situ resources such as water volatile and mineral. Evidence for water ice in Permanently Shadowed Regions (PSRs) on the Moon is both direct and indirect, and derives from multiple past missions including Lunar Prospector, Chandrayaan-1 and LCROSS. Recent lunar CubeSats missions proposed through the Space Launch Systems (SLS) such as Lunar Flashlight, LunaH-Map and Lunar Ice-Cube, will help improve our understanding of the spatial distribution of water ice in those lunar cold traps. However, the spatial resolution of the observations from these SLS missions is on the order of one to many kilometres. In other words, they can miss smaller (sub-km) surficial deposits or near-surface deposits of water ice. Given that future lunar landers or rovers destined for PSRs will likely have limited mobility (but improved landing precision), there is a need to improve the spatial accuracy of maps of water ice in PSRs. The VMMO (Volatiles and Mineralogy Mapping Orbiter) is a semiautonomous, low-cost 12U lunar Cubesat being developed by a multi-national team funded through European Space Agency (ESA) for mapping lunar volatiles and mineralogy at relatively high spatial resolutions. It has a potential launch in 2023 as part of the ESA/SSTL lunar communications pathfinder orbiter mission. This paper presents the work carried out so far on VMMO concept design and development including objectives, profile, operations and spacecraft payload and bus.
A number of low-cost open-loop slew control algorithms have been developed for prolate spinning spacecraft using single-thruster actuation. Robustness analysis indicates that these algorithms have high sensitiveness over thruster firing time error, spacecraft inertia error, and especially spin rate perturbations. This paper proposed two novel feedback slew algorithms, Feedback Half-Cone and Feedback Sector-Arc Slew, built on the existing open-loop algorithms and they use attitude and angular velocity feedback to improve robustness. As presented, after the first thruster actuation initiate the spin-axis precession, the feedback slew algorithms take attitude and spin-rate feedback to estimate the angular momentum and predict the spin-axis attitude during the slew. These techniques contribute to improve the cancelation thrust impulse accuracy and reduce the final nutation error. Simulations for a Penetrator mission scenario validate these feedback algorithms and show their slew performance and robustness over the perturbations mentioned above. It is proved that the attitude feedback greatly improves the slew accuracy and robustness.
is paper presents a modular design concept of autonomous navigation software for planetary rovers. e software covers major navigation functions such as autonomous localisation and mapping, visual rock detection, and path planning. e proposed design includes a generic data pipeline which produces a sequence of data products based on sensory raw data. To effectively and efficiently integrate the various design elements, Robot Operating System (known as ROS) is used as the middleware framework to implement the generic data pipeline and synthesize various navigation functions in terms of ROS nodes. e paper also presents test results of the proposed software implemented within the Surrey Rover Autonomous Software and Hardware Testbed (SMART) based on real and artificial data.
Observations of highly red-shifted 21-cm hydrogen signals have been suggested as the only means to probe the early Universe from recombination to reionization. During this era, called the Dark Ages, the Universe consisted of neutral hydrogen gas and was opaque to light. It did not become transparent, as we see it today, until reionization was completed. The Dark Ages was the time period when matter clumped together, the very first stars and black holes were born, and, eventually, the first galaxies were formed. To enable observations of the Dark Ages is therefore one of the top priorities in cosmology and astrophysics. Today, the cosmological 21-cm signals are highly red-shifted and should peak in the FM radio band. Observing the Dark Ages from Earth is therefore next to impossible, due to man-made radio frequency interference (RFI) and ionospheric disturbances. To efficiently block the RFI, which would otherwise overwhelm the weak cosmological signal; it has been proposed to use the Moon as a radio shield and either place a satellite equipped with an ultra-sensitive radio instrument in lunar orbit or to deploy a large low-frequency radio array on the far-side of the Moon. Such missions are technically challenging and expensive and have so far failed to gain support from any national or international space program. Our goal is therefore to use a constellation of small inexpensive satellites in lunar orbit to collect pathfinder data, which would demonstrate EPSC Abstracts Vol. 9, EPSC2014-798, 2014 European Planetary Science Congress 2014 c Author(s) 2014 EPSC European Planetary Science Congress the feasibility of using the Moon as a radio shield, and map out the spatial extent of this RF quiescent zone to support future missions to explore the cosmos. This paper examines the design and radio payload of this mission. Alternative orbits, constellation and payload designs are analyzed to optimize the mission for performance and cost.
Spectrum sensing is one of the key technologies to realize dynamic spectrum access in cognitive radio (CR). In this paper, a novel database-augmented spectrum sensing algorithm is proposed for a secondary access to the TV White Space (TVWS) spectrum. The proposed database-augmented sensing algorithm is based on an existing geo-location database approach for detecting incumbents like Digital Terrestrial Television (DTT) and Programme Making and Special Events (PMSE) users, but is combined with spectrum sensing to further improve the protection to these primary users (PUs). A closed-form expression of secondary users' (SUs) spectral efficiency is also derived for its opportunistic access of TVWS. By implementing previously developed power control based geo-location database and adaptive spectrum sensing algorithm, the proposed database-augmented sensing algorithm demonstrates a better spectrum efficiency for SUs, and better protection for incumbent PUs than the exiting stand-alone geo-location database model. Furthermore, we analyze the effect of the unregistered PMSE on the reliable use of the channel for SUs.
This work proposes a robust visual odometry method for structured environments that combines point features with line and plane segments, extracted through an RGB-D camera. Noisy depth maps are processed by a probabilistic depth fusion framework based on Mixtures of Gaussians to denoise and derive the depth uncertainty, which is then propagated throughout the visual odometry pipeline. Probabilistic 3D plane and line fitting solutions are used to model the uncertainties of the feature parameters and pose is estimated by combining the three types of primitives based on their uncertainties. Performance evaluation on RGB-D sequences collected in this work and two public RGB-D datasets: TUM and ICL-NUIM show the benefit of using the proposed depth fusion framework and combining the three feature-types, particularly in scenes with low-textured surfaces, dynamic objects and missing depth measurements.
The dual-reciprocating drill (DRD) is a biologically-inspired low-mass alternative to traditional drilling techniques, using backwards-facing teethed halves to grip the surrounding substrate, generating a traction force that reduces the required overhead penetration force. Previous experiments using a proof-of-concept test bench have provided evidence as to the significant role of sideways movements and lateral forces in improving drilling performance. The system is also progressing to a first system prototype concept, in which an actuation mechanism is integrated within the drill heads. To experimentally determine the effect of lateral motions, a new internal actuation mechanism was developed to allow the inclusion of controlled sideways movements, resulting in the creation of the circular and diagonal burrowing motions. This paper presents an investigation into the performance of the reciprocation and burrowing motions by testing them in a planetary regolith simulant. Analysis of force sensor measurements has shown a relationship between the penetration and traction forces and the internal friction of the mechanism and depth achieved. These tests have also experimentally demonstrated the benefit of lateral motions in drilling performance, with both the burrowing mechanisms and drilling tests performed at an angle able to penetrate further than traditional vertical reciprocation, leading to the proposition of new burrowing and diagonal drilling mechanics. From this, a new fully integrated system prototype can be developed which incorporates lateral motions that can optimise the drilling performance.
Identification of the wheel sinkage of exploration rovers provides valuable insight into the characteristics of deformable soils and thus the ease of traversal is also identified. In this paper we propose a simple vision based approach that robustly detects and measures the sinkage of any shaped wheel in real-time and with little sensitivity to various operating conditions. The method is based on color-space segmentation to identify the wheel contour and consequently the depth of the sinkage. In addition, our approach also provides a dynamic sinkage analysis which potentially allows for the identification of non-geometric hazards. The robustness of the algorithm has been validated for poor lighting, blurring, and background noise. The experimental results presented are for a hybrid legged wheel from our in-house single-wheel test-bed.
Automated planning has been applied to numerous fields such as computer games, industrial robotics and even highprofile missions like planning and scheduling activities for Martian rovers. A current trend among the researchers is to apply automated planning in multiple space systems that work together in a coordinated fashion so as to attain highly complex mission goals. Even though automated planning and scheduling algorithms are mature in industrial scenarios and robotics, little consideration has been given to multiple-agent space applications. In this paper, we describe the development of a domain configurable planner which can be used for different space mission comprising of multiple systems i.e. satellites or rovers. The multiagent planning systems uses agent based modeling techniques, hierarchical task network (HTN) planning and a mixed approach from centralized and distributed planning. The initial results from the prototype planner are also discussed.
Attitude determination is one of the most important prerequisites for the implementation of an air bearing table. In this context, computer vision is shown to be an enabling technology; a cost-effective monocular camera vision system, including hardware setup and navigation software, has been developed to determine the attitude of the air bearing table. Both infrared light-emitting diodes and filter are selected to simplify image processing, thereby maximizing the attitude update rate.Afiducial marker system uses five infrared light-emitting diodes with four in the same plane and the fifth outside the plane. This noncoplanar design not only improves the attitude determination accuracy, but also provides an element of robustness via a fiducial marker fault diagnosis and process method in case one of the lightemitting diodes is obscured by the top balance mass or is faulty. The static experimental results show that the system can provide attitude accuracy of 0.06 deg and angular velocity accuracy of 0.15 deg /s with an attitude update rate of at least 10 Hz. Finally, a yaw-axis maneuver is performed to demonstrate the system performance under dynamic conditions. The developed system could be reused to support testing for other scientific space missions, which represents a major added value of this work. Copyright © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
This work investigates the effects of high-powered ultrasonics in granular material. The aim is to facilitate penetration in granular material in low-mass/ low-gravity environments. The results show that the weight on bit requirement for penetration is significantly reduced on application of direct ultrasonic vibration, especially in high relative density substrates.
Chang’E-3 (CE-3) was the third mission by China to explore the Moon which had landed two spacecraft, the CE-3 lander and Yutu rover on the lunar surface in late 2013. The paper presents analytical results of high-resolution terrain data taken by CE-3’s onboard cameras. The image data processing aims to extract sinkage profiles of the wheel tracks during the rover traverse. Further analysis leads to derivation or estimation of lunar soil physical properties (in terms of strength and stiffness) based on the wheel sinkage, despite the fact Yutu does not possess in situ soil measurement instruments. Our findings indicate that the lunar soil at the CE-3 landing site has similar stiffness to what is measured at the Luna 17 landing site but has much less strength compared to the Apollo 15 landing site.