AI and Robotics (STAR LAB)

We are the Space Technology for Autonomous and Robotic systems Laboratory (STAR LAB) led by Professor Yang Gao.

STAR LAB brochure

(3.2 MB .PDF)


We are a team of academic scholars, engineers and roboticists whose vision is to build on four decades of R&D heritage in small spacecraft engineering within the Surrey Space Centre and extend this philosophy to advance autonomous systems and robotics for space. We also look at transfer of our knowledge and technologies to terrestrial applications and to help maximize impact of our research work.

The STAR LAB leads Surrey's involvement within the UK-RAS Network, and was an active participant and co-organiser to the UK Robotics Week. We are also the hosting research lab of the UKRI/UKSA hub on the Future AI and Robotics for Space (FAIR-SPACE). Our other international community activities include leading the IEEE-CIS Task Force on Intelligent Space Systems and Operations, UK-RAS White Paper on Space Robotics, TAROS 2017, etc.

International recognitions

Our Lab and its members have received many national and international recognitions. For example, our lab director Professor Yang Gao 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 Prof Gao's supervision has been internationally rewarded including:

  • International Astronautical Federations (IAF) 3AF Edmond Brun Silver Medal in 2013
  • Committee on Space Research (COSPAR) Outstanding Paper Award in 2016
  • First Prize of UKSEDS Lunar Rover Competition in 2017
  • Joint Winner of ESA SysNova Challenge on Lunar CubSat Exploration in 2018
  • Finalist of IEEE/ASME's AIM Best Paper Award in 2019
  • Top 3 worldwide of ESA/Stanford Pose Estimation Challenge in 2019
  • First Prize of Best Poster Award at IEEE-ICRA Space Robotics Workshop in 2020, etc.

Enabling technologies

Our main research expertise and key research products include the following:

  • Our research leads to technologies for low-computation, high-accuracy 3D mapping and perception, resource-aware computation and data assimilation for parameter tuning in order to address challenges imposed by the extreme environments and design constraints of spacecraft and space missions.
  • Visual sensing using optical monocular/stereo cameras, 2D/3D LIDAR, and RGB-D sensors for visual odometry or pose estimation. (Our technique is ranked 2nd place for real-world dataset and 3rd place for synthetic dataset in the ESA/Stanford Pose Estimation Challenge 2019).
  • Visual perception based on cognitive vision and saliency techniques for thematic feature extraction, sinkage prediction, and terrain classification.
  • Planetary Monocular SLAM (PM-SLAM) for long range navigation of surface rovers (IAF's 3AF Edmond Brun Silver Medal 2013).
  • Major funded research projects and contributions to real-world space missions: ESA ExoMars mission’s PanCam payload and Phase A study; ESA Proba3 mission’s FLLS payload; UKSA funded CREST-1, NSTP2, and CREST-3 projects; Airbus funded OOA project; CNSA Chang’E3 mission’s PanCam data analytics; UKRI/UKSA funded Future AI & Robotics for Space (FAIR-SPACE) project.


L. Dai, J. Liu, Z. Ju and Y. Gao, "Iris Centre Localization Using Energy Map with Image Inpaint Technology and Post-Processing Correction," in IEEE Access, vol. 8, pp. 16965-16978, 2020. DOI: 10.1109/ACCESS.2020.2966722.

Robert Skilton, Yang Gao, Combining object detection with generative adversarial networks for in-component anomaly detection, Fusion Engineering and Design, Volume 159, 2020,

Miranda Bradshaw, Yang Gao, Kevin Homewood, “Interpolation methods for tracking spacecraft in ultra-tight formation”, Journal of Astronomical Telescopes, Instruments, and Systems, 5(2), 028003, 2019, doi: 10.1117/1.JATIS.5.2.028003.

Pedro F. Proença, Yang Gao, "Probabilistic RGB-D odometry based on points, lines and planes under depth uncertainty”, Robotics and Autonomous Systems, 10 March 2018,

Affan Shaukat, Yang Gao, Jeffrey A. Kuo, Bob A. Bowen and Paul E. Mort, "Visual Classification of Waste Material for Nuclear Decommissioning," Robotics and Autonomous Systems, Volume 75, Part B, Pages 365-378, 2016, doi: 10.1016/j.robot.2015.09.005.

Yang Gao, Steven Chien, Review on space robotics: Toward top-level science through space exploration. Science Robotics, 2, eaan5074 (2017). 

Conrad Spiteri, Affan Shaukat and Yang Gao "Structure Augmented Monocular Saliency for Planetary Rovers," Robotics and Autonomous Systems, Vol. 88, 1-10, 2017, doi:10.1016/j.robot.2016.11.013.

Affan Shaukat, Peter Blacker, Conrad Spiteri, and Yang Gao "Towards Camera-LIDAR Fusion-Based Terrain Modelling for Planetary Surfaces: Review and Analysis," Sensors, 16(11), 2016, doi:10.3390/s16111952.

Yang Gao, Conrad Spiteri, Chun-Lai Li and Yong-Chun Zheng, “Lunar Soil Strength Estimation based on Chang’E3 Images”, Advances in Space Research, Volume 58, Issue 9, p. 1893-1899, 2016, doi: 10.1016/j.asr.2016.07.017.

Abhinav Bajpai, Affan Shaukat, Guy Burroughes, Yang Gao, Planetary Monocular Simultaneous Localization and Mapping (PM-SLAM), Journal of Field Robotics, Volume 33, Issue 2, pages 229–242, 2015, DOI: 10.1002/rob.21608.

Conrad Spiteri, Yang Gao, Said Al-Milli, and Aridane Sarrionandia de León, Real-time Visual Sinkage Detection for Planetary Rovers, Robotics and Autonomous Systems, Vol 72, pp. 307–317, 2015.

Yang Gao, Conrad Spiteri, Minh-Tri Pham, and Said Al-Milli, A Survey on Recent Object Detection Techniques Useful for Monocular Vision-based Planetary Terrain Classification, Robotics and Autonomous Systems, Vol. 62, Issue 2, pp. 151-167, 2013, 10.1016/j.robot.2013.11.003.

Peter Yuen, Yang Gao, Andrew Griffiths, Andrew Coates, Jan-Peter Muller, Alan Smith, Dave Walton, Craig Leff, Barry Hancock and Dongjoe Shin, ExoMars PanCam: Autonomy and Computational Intelligence, IEEE Computational Intelligence Magazine, Volume 8, Issue 4, pp. 52-61, Nov. 2013.

Dario L. Sancho-Pradel and Yang Gao, “A Survey on Terrain Assessment Techniques for Autonomous Operation of Planetary Robots”, Journal of British Interplanetary Society, Vol. 63, No. 5/6, pp. 206-217, May/June 2010.

  • Our research leads to technologies for hardware/software reconfiguration and self-verification in real time.
  • Autonomous software architecture, domain-independent, generic and reconfigurable, based on rational agents for complex space systems such as multi-satellite and multi-rover scenario.
  • Advanced software agents for learning and planning capabilities.
  • Ontology-based complex system modeling through SySML.
  • Major UKRI-EPSRC funded research projects: FAIR-SPACE RAI hub grant; Industrial 6th Sense grant; Autonomous & Intelligent Systems Programme; Impact Acceleration Account; Strategic Collaboration Award; Capital Equipment Grant.


Yang Gao, (Ed.) Contemporary Planetary Robotics – An Approach to Autonomous Systems, pp. 1-

450, Berlin: Wiley-VCH, ISBN-10: 3527413251, ISBN-13: 978-3527413256, August 2016.

Guy Burroughes and Yang Gao, "Ontology-Based Self-Reconfiguring Guidance, Navigation, and Control for Planetary Rovers". AIAA Journal of Aerospace Information Systems, Vol. 13, No. 8, pp. 316-328, 2016, doi: 10.2514/1.I010378.

Aitken, Jonathan, Sandor Veres, Affan Shaukat, Yang Gao, Elisa Cucco, Louise Dennis, Michael Fisher, Jeff Kuo, Thomas Robinson, and Paul Mort. "Autonomous nuclear waste management." IEEE Intelligent Systems, 2018, Vol. 33, Issue 6, 10.1109/MIS.2018.111144814.

Dennis LA, Fisher M, Aitken JM, Veres SM, Gao Y, Shaukat A, Burroughes G., Reconfigurable Autonomy, KI - Künstliche Intelligenz, Springer, 28 (3), pp. 199-207, 2014.

Juan M. Delfa Victoria, Simone Fratini, Nicola Policella, Oskar von Stryk, Yang Gao and Alessandro Donati, Planning Mars Rovers with Hierarchical Timeline Networks, Acta Futura, Issue 9, 21-29, 2014.

Yang Gao, Nicola Policella, and Frank Kirchner, Computational Intelligence for Space Systems and Operations, IEEE Computational Intelligence Magazine, Volume 8, Issue 4, pp. 9-11, Nov. 2013.

Yang Gao, Renato Samperio, Karin Shala and Ye Cheng, “Modular Design for Planetary Rover Autonomous Navigation Software using ROS”, Acta Futura, Issue 5, pp. 9-16, 2012.

Yifan Luo, Jinguo Liu, Yang Gao and Z Lu, Smartphone-Controlled Robot Snake for Urban Search and Rescue, Lecture Notes in Computer Science, 8917, pp. 352–363, 2014.

Angadh Nanjangud, Peter C. Blacker, Saptarshi Bandyopadhyay, and Yang Gao, "Robotics and AI enabled On-Orbit Operations with Future Generation of Small Satellites" Proceedings of the IEEE, 106 (3), pp. 429-439, 2018, 10.1109/JPROC.2018.2794829.

C. Saunders, D. Lobbb, M. Sweeting, Y. Gao, Building Large Telescopes In Orbit Using Small Satellites, Acta Astronautica, 141, 183-195, 2017.

Biomimetic mechanism and robot soil interaction
  • Our research leads to technologies for energy-optimised locomotion mechanisms and control.
  • Pioneering bio-inspired Dual Reciprocating Drilling (DRD) technology - also known as the ‘wasp drill’ - allowing deep drilling with flexible deployment mechanism in low-gravity environments, and low-mass sampling tool suitable for small space vehicles. (COSPAR Outstanding Paper Award 2016; Finalist of IEEE/ASME's AIM Best Paper Award 2019; Exhibition at National Science Museum 'Antenna' gallery).
  • Innovative surface Mobile Active Rover Chassis for Enhanced Locomotion (MARCEL), capable of negotiating with loose soil and rugged terrains using minimal actuation.
  • Rigorous and systematic preparation methodologies for planetary soil simulants, ranging from Martian compressible soil to icy lunar regolith.
  • Vision based techniques for soil characterisation and physical property estimation.
  • Major funded research projects and contributions to real-world space missions: ESA ExoMars mission’s sampling payload testing; ESA Lunar Polar Sample Return (LPSR) mission’s L-GRASP payload testing; CNSA’s Chang’E3 mission terrain image analytics; ESA’s ACT grant on Bionics and Space Systems; NPI/OHB grant on innovative deep drilling; RAEng project on low-cost sampling; UKRI/UKSA funded FAIR-SPACE project.


Craig Pitcher and Yang Gao, Physical Properties of Icy Materials, in Outer Solar System: Prospective Energy and Material Resources, Springer-Verlag, pp. 1-940, ISBN: 978-3-319-73844-4, 2018, doi:10.1007/978-3-319-73845-1.

David Firstbrook, KevinWorrall, Ryan Timoney, Francesc Suñol, Yang Gao and Patrick Harkness, An experimental study of ultrasonic vibration and the penetration of granular material, Royal Society Proceedings A: Mathematical, Physical and Engineering Sciences, 473(2198), 2017, doi: 10.6084/m9.figshare.c.3683191.

Craig Pitcher and Yang Gao, First implementation of burrowing motions in dual-reciprocating drilling using an integrated actuation mechanism, Advances in Space Research, Volume 59, Issue 5, p. 1368-1380, 2017, doi:10.1016/j.asr.2016.12.017

Norbert Kömle, Craig Pitcher, Yang Gao and Lutz Richter. Study of the Formation of Duricrusts on the Martian Surface and Their Effect on Sampling Equipment. ICARUS, Volume 281, p. 220-227, 2017, doi: 10.1016/j.icarus.2016.08.019.

Craig Pitcher, Norbert Kömle, Otto Leibniz, Odalys Morales-Calderon, Yang Gao, and Lutz Richter. "Investigation of the properties of icy lunar polar regolith simulants." Advances in Space Research, Volume 57, Issue 5, Pages 1197–1208, 2016, doi:10.1016/j.asr.2015.12.030.

Craig Pitcher and Yang Gao, Analysis of drill head designs for dual-reciprocating drilling techniques in planetary regolith, Advances in Space Research, Volume 56, Issue 8, pp. 1765–1776, 2015. COSPAR Outstanding Paper Award

Liu J, Wang Y, Ma S, Luo Y, Gao Y, Comments on "sidewinding with minimal slip: snake and robot ascent of sandy slopes", Robot, 37(2), pp. 254-256, 2015.

Thibault Gouache, Yang Gao, Pierre Coste, Yves Gourinat, First experimental investigation of dual reciprocating drilling in planetary regolith: proposition of penetration mechanics, Planetary and Space Science, Volume 59, Issue 13, pp. 1529-1541, October 2011.

Thibault P. Gouache, Christopher Brunskill, Gregory P. Scott, Yang Gao, Pierre Coste, Yves Gourinat, Regolith simulant preparation methods for hardware testing, Planetary and Space Science, Volume 58, Issues 14-15, pp. 1977-1984, 2010.

Y. Gao, M.N.Sweeting, S. Eckersley, J.F.V. Vincent, A “micro” concept for a planetary penetrator & drill package, in Penetrometry in the Solar System II, Gunter Kargl, Norbert I. Komle, Andrew J. Ball, Ralph D. Lorenz (Ed.), Vienna: Austrian Academy of Sciences Press, pp. 83-92, 2009, ISBN 978-3-7001-6531-6.

Thibault Gouache, Yang Gao, Yves Gourinat and, Pierre Coste, Wood Wasp Inspired Space and Earth Drill, in Biomimetics, Learning from Nature, pp.467-486, March 2009, ISBN 978-953-307-025-4.

N.I. Kömle, E. Kaufmann, G. Kargl, Y. Gao and X. Rui, “Development of thermal sensors and drilling systems for lunar and planetary regoliths”, Advances in Space Research, Volume 42, Issue 2, pp. 363-368, July 2008.

N.I. Komle, E. S. Hutter, G. Kargl, H. Ju, Y. Gao, J. Grygorczuk, Development of Thermal, Sensors and Drilling Systems, For Application On Lunar Lander Missions, Earth, Moon and Planets, 103, pp. 119-141, 2008.

  • Low-cost attitude control for spinning space vehicles (such as kinetic penetrators or multi-U CubeSat) using minimum one actuator.
  • State-of-the-art slew algorithms including Extended Half Cone, Dual Cone, Sector Arc, and Spin Synch.
  • Major funded research projects and contributions to real-world space mission: Airbus funded R&D on software and hardware testbed for underactuated slew control; Surrey led Strand-1 CubeSat mission’s slew control experiment.


Juntian Si, Yang Gao, Abadi Chanik, Feedback Slew Algorithms for Prolate Spinners Using Single-Thruster, Acta Astronautica, Vol 144, pp. 39-51, March 2018,

Juntian Si, Yang Gao, Abadi Chanik. Slew Control of Prolate Spinners Using Single-Magnetorquer, AIAA Journal of Guidance, Control, and Dynamics, Vol. 39, No. 3, pp. 719-727, 2016.

Chanik, A., Gao, Y., Si, J., "Modular testbed for spinning spacecraft," AIAA Journal of Spacecraft, and Rockets, Vol. 54, No. 1, pp. 90-100, 2017, doi: 10.2514/1.A33586.

Yun-Hua Wu, Yang Gao, Jia-Wei Lin, Robin Raus, Shi-Jie Zhang and Mark Watt, A Low Cost, High Performance Monocular Vision System for Air Bearing Table Attitude Determination, AIAA Journal of Spacecraft and Rockets, Vol. 51, No. 1, pp. 66-75, 2014.

Robin Raus, Yang Gao, Yunhua Wu, Mark Watt, Analysis of state-of-the-art single-thruster attitude control techniques for spinning penetrator, Acta Astronautica, Volume 76, pp. 60-78, 2012.

Yunhua Wu, Yang Gao, Robin Raus, Mark Watt, “A Trade-off Study of Single Thruster Attitude Control Algorithms for Prolate Spinning Spacecraft”, AIAA Journal of Guidance, Control, and Dynamics, vol. 35, no.4, pp. 1143-1157, 2012.

R.A. Gowen, A. Smith, A.J. Coates, I.A. Crawford, R.F. Scott, P.D. Church, Y. Gao,  W.T. Pike, J. Flanagan,  Development of kinetic penetrators for exploration of airless solar system bodies, in Penetrometry in the Solar System II, Vienna: Austrian Academy of Sciences Press, pp. 83-92, 2009, ISBN 978-3-7001-6531-6.

Key space systems

The technologies developed at STAR Lab are used to realise next generation spacecraft and vehicles, including rovers, robotic arms, wasp drills and penetrators.

Robotic vehicle driving on sand
  • Multiple small to medium-sized rovers with different chassis, e.g. Mecanum wheeled, normal wheeled, tracked (ranging from 20 to 100kg each).
  • Robotic payloads: multi-DoF robotic arm, gripper, drill sampler.
  • Sensors: monocular and stereo camera, 2D and 3D LIDAR, IMU, differential GPS.
  • Operating standardised mid-ware ROS for testing of modular autonomy functions and/or applications.

Robotic vehicle driving on the moon
  • Active suspension design to allow crawling and climbing behaviours.
  • 4- wheeled active rover chassis to improve crossing capabilities over rough terrain and loose soil with a minimal amount of actuation (or comparable to rocker-bogie design with passive suspension).
  • Deep reinforcement learning-enabled GNC algorithms that can learn traversability features and automatically tune the GNC parameters.

Wasp bot for STAR LAB
  • Planetary drill inspired by wood wasp ovipositor mechanism.
  • Based on Dual Reciprocating Drilling (DRD) which does not rely on overhead force to operate.
  • Lighter weight, higher power efficiency than conventional drills such as rotary and percussive.
  • Advantageous for low-gravity mission scenarios such as the Moon, asteroids and comets.


Yang Gao, Tom Frame and Craig Pitcher, Piercing the Extraterrestrial Surface: Integrated Robotic Drill for Planetary Exploration, IEEE Robotics and Automation Magazine, 22(1): 45-53, 2015.

Y. Gao, A. Ellery, M.  Jaddou, J. Vincent, and S. Eckersley “A Planetary Micro-Penetrator Concept Study with a Biomimetic Drill & Sampler Subsystem,” IEEE Trans. Aerospace & Electronic Systems, Vol. 43, No. 3, pp. 875-885, Nov 2007.

Y. Gao, A. Ellery and M. Sweeting, J. Vincent, “Bio-inspired Drill for Planetary Sampling: Literature Survey, Conceptual Design and Feasibility Study,” AIAA J. Spacecraft & Rockets, Vol. 44, No. 3, pp. 703-710, 2007.

Y. Gao, A. Ellery, M.  Jaddou, J. Vincent and S. Eckersley, “A Novel Penetration System for in situ Astrobiological Studies,” International Journal of Advanced Robotic Systems, Vol. 2, No. 4, pp. 281-286, 2005.

  • The probe (~10kg) free falls and penetrates into target planetary bodies at hundreds of metres per second, and a small angle of attack (less than 8 degrees) is permitted.
  • Fully instrumented with engineering and scientific payload.
  • Involved in MoonLITE, LunarEX/NET mission proposals and the UK Penetrator Consortium.


A. Smith, et. al., Lunar Net – A proposal in response to an ESA M3 call in 2010 for a medium sized mission, Experimental  Astronomy, Volume 33, Issue 2-3 , pp. 587-644, 2011.

Robert Gowen, et. al., “Penetrators for in-situ sub-surface investigations of Europa”, Advances in Space Research, 48(4):725-742, 2011

Smith A, et. al., “LunarEX-a proposal to cosmic vision”, Experimental Astronomy, Volume: 23, Issue: 3, pp. 711-740, March 2009

R.A. Gowen, et. al., Development of kinetic penetrators for exploration of airless solar system bodies, in Penetrometry in the Solar System II, Vienna: Austrian Academy of Sciences Press, pp. 83-92, 2009, ISBN 978-3-7001-6531-6.

Y. Gao, A. Phipps, M. Taylor, J. Clemmet, I. A. Crawford, A. J. Ball, L. Wilson, D. Parker, M. Sweeting, A. Curiel, P. Davies, A. Baker, T. Pike, A. Smith, and R. Gowen, “Lunar Science with Affordable Small Spacecraft Technologies: MoonLITE & Moonraker”, Planetary & Space Science, Volume 56, Issues 3-4, pp. 368-377, March 2008.

Space and non-space missions

An artistic impression of the VMMO concept

The ESA Volatile and Mineralogy Mapping Orbiter (VMMO) is a lunar CubeSat mission among the two joint winners of ESA's SysNova Challenge on LUnar Cubesats for Exploration (LUCE) in 2017.

This proposed mission aims to address several key aspects of future lunar exploration with planned launch in 2023: Mapping of relevant in-situ resources and volatiles in sufficient quantities to be operationally useful (fuel, life-support) for future sustained surface missions, and developing enabling technologies for beyond-LEO CubeSats.

Professor Yang Gao, Director of STAR LAB is the CubeSat platform PI of the VMMO Phase A funded by ESA, as well as the lead of OBC/Autonomy subsystem.


Yang Gao, Roman V. Kruzelecky, Piotr Murzionak, Craig Underwood, Chris Bridges, Roberto Armellin, Andrea Luccafabris, Jonathan Lavoie, Ian Sinclair, Gregory Schinn, Edward Cloutis, Johan Leijtens, Roger Walker and Johan Vennekens, Lunar “Volatile and Mineralogy Mapping Orbiter (Vmmo)” Mission, IAC-19-A3.2B.6x50377, Proc. International Astronautical Conference, Washington DC, USA, October 2019. 

Exomars robot

The ExoMars mission aims to demonstrate key planetary robotics technologies such as rover autonomy and deep drilling. The STAR LAB was involved in the ESA funded Phase A study, has been involved in the UK-led PanCam payload onboard the ExoMars 2022 rover, as well as has been developing next generation rover locomotion, autonomy and planetary drilling technologies in collaboration with space industry such as Airbus DS and OHB. 

The follow-on studies have been looking at next-generation GNC for planetary rover to achieve faster travelling speed and longer traverse distance based on higher autonomy capabilities through robotic vision and machine learning techniques. Future missions that will benefit from these advancement include Mars or Phobos sample return mission.


Peter Yuen, Yang Gao, Andrew Griffiths, Andrew Coates, Jan-Peter Muller, Alan Smith, Dave Walton, Craig Leff, Barry Hancock and Dongjoe Shin, ExoMars PanCam: Autonomy and Computational Intelligence, IEEE Computational Intelligence Magazine, Volume 8, Issue 4, pp. 52-61, Nov. 2013.

Robot in space

The Proba3 mission aims to demonstrate key technologies that enable precision formation flying between two spacecraft for the first time, such as high accuracy measurement system.

The STAR Lab has been involved in the calibration of the Lateral and Longitudinal Sensor (FLLS) onboard one of the Proba3 spacecraft and its ground testing. FLLS could allow large-scale structures to be deployed and maintained in space, monitoring structural distortion before, during and after deployment, and providing in-flight corrections to data collection.

Examples of such future applications include in-orbit observatories, positioning of telecommunication satellite antennas, and deployable mechanisms on Moon or Mars missions.


M. J. Bradshaw, Y. Gao, K. Homewood, Performance modelling of the fine lateral and longitudinal sensor (FLLS) for ESA's PROBA-3 mission, SPIE Optical Engineering, Aug 2018, DOI: 10.1117/12.2320571.

M. J. Bradshaw, Y. Gao, K. Homewood, Fine Lateral and Longitudinal Sensor (FLLS) on-board ESA’s PROBA-3 mission, 68th International Astronautical Congress, Adelaide, September 2017.

Roscosmos robot

The LunaResurs mission aims to land at the lunar south pole to search for minerals and water. The STAR Lab is involved in developing the landing sensor called LEIA, a LIDAR instrument that enables the lander to avioid uneven terrain and land safely.

The LEIA (or LIDAR for Extra-terrestrial Imaging Applications) will provide a 3D map of the lunar surface from two altitudes during landing: 1.3 km and 250 m, with resolutions of 1.0 m and 0.1 m respectively. Due to launch in 2021, the LunaResurs will be the first mission applies most of the components in the LIDAR in space or on the lunar surface.

Subject to a rigorous test campaign, this mission will pave the way for more extensive applications of LIDAR technologies in future space missions.


M. J. Bradshaw, Y. Gao, K. Homewood, LEIA: The Landing LiDAR for ESA-Roscosmos' LunaResurs mission, 68th International Astronautical Congress, Adelaide, September 2017.

Nuclear industry facility

The STAR LAB has been transferring knowledge and space AI robotics into the industrial sector, by offering:

  • Reconfigurable autonomous software architecture for operation of industrial plants where design requirements and challenges are similar to relevant space applications.
  • Customised robotic vision system for autonomous inspection and classification of anomalies going through the plant processes (such as “sort and segregate” in nuclear plants or robotic inspector for chemical plants).
  • Customised machine vision system for autonomously detection, measurement and tracking of the dynamic behaviours (such as gas bubbles of the liquid pond in nuclear decommissioning sites or gas leaks in chemical plants).

Agriculture applications image

The STAR Lab has been transferring and integrating space robotics and autonomou systems technologies into the agriculture sector, by developing:

  • Computer vision techniques to detect anomalies in crops and related agricultural applications including spectrum based segmentation and automatic selection using clustering algorithm. For examples, leaf close up image is segmented and analysed whereby diseased sections are identified and extracted and diseased / Healthy leaf metrics are calculated
  • Autonomous rovers and navigation capabilities applicable to agriculture robots
  • Integrating satellite, aerial and ground based data systems and robotic platforms.

STAR LAB Director

Yang Gao profile image

Professor Yang Gao

Professor of Space Autonomous Systems; Wiley JFR Editor-in-Chief; United Nations Space4Women Mentor