Robots that can identify materials and map unknown environments could aid nuclear and defence sectors
Robots that can see beyond human vision, build live 3D maps of unknown environments and identify what objects are made of are being developed by researchers at the University of Surrey, opening new possibilities for applications in nuclear inspection, rail and building safety or search and rescue in combat zones.
Working in collaboration with Kent-based company, Industrial 3D Robotics, and spectroscopy specialists, IS-Instruments, the team is combining advanced imaging and AI mapping technologies that give robots material awareness of their surroundings.
Unlike conventional cameras, which mimic human vision using red, green and blue light, the robots are equipped with hyperspectral vision, meaning they can capture information across many more wavelengths, including parts of the infrared and ultraviolet spectra. These cameras record the unique spectral fingerprint of materials, helping robots distinguish rust from dirt, identify suspicious objects or freshly disturbed ground, and even tell visually identical pills apart.
The systems combine the visual information with Simultaneous Localisation and Mapping (SLAM) – a technique that enables autonomous robots to navigate and map unfamiliar environments in real time – alongside FeatureSLAM, an AI-powered system that helps robots create highly detailed, realistic 3D maps with a greater understanding of the objects and environments around them.
To demonstrate the technology, researchers at the Surrey Institute for People-Centred AI mounted the system onto a Boston Dynamics Spot robot dog, enabling it to move through an environment while building a live 3D map layered with hyperspectral material data.
Most robots today still see the world in a very human way – using the equivalent of red, green and blue vision. What we’re doing is giving robots access to far more information about their surroundings, allowing them to understand not just the shape of an environment, but what objects are actually made of.Christopher Thirgood, Postgraduate Researcher and lead developer
“In studies we’ve carried out so far, we found that material-based sensing improved robot localisation accuracy by 16 per cent compared with existing approaches.
The approach could have major applications in hazardous or complex environments, particularly in the nuclear, rail and industrial sectors, where understanding material properties remotely could improve safety and decision-making.
Robots That Can See What Objects are Made of and Map Unknown Environments | University of Surrey
The team has recently submitted a patent and is now working with industrial partners to further develop the technology into deployable commercial systems.
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Notes to editors
- Christopher Thirgood and Professor Simon Hadfield are available for interview; please contact mediarelations@surrey.ac.uk to arrange.
- Images are available upon request
The Surrey Institute for People-Centred AI (PAI)
PAI is the founding pan-University Institute at the University of Surrey. It brings together core AI-related expertise in audio-visual and signal processing, computer science, and mathematics, with its domain expertise across engineering and physical sciences, human and animal health, law and regulation, business, finance and the arts and social sciences.
PAI puts people at the heart of AI. Our founding tenet is that Artificial Intelligence must be shaped by the people it seeks to serve. AI will never replace people, but it has the potential to augment our capabilities and serve society based on an inclusive, diverse and fair approach.
PAI, with our Centre for Vision, Speech and Signal Processing (CVSSP) is the foundation of Surrey’s ranking 1st in the UK and 3rd in Europe for Computer Vision, and 3rd in UK for CV and AI, 7th in Europe (CSrankings.org, sourced November 2025).
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