Thomas Stone
Papers
1
Total Citations
23
H-Index
1
About
Thomas Stone is a roboticist whose research focuses on robust place recognition and localisation for agile, outdoor robots operating in challenging natural environments. His most cited work, "Skyline-based localisation for aggressively manoeuvring robots using UV sensors and spherical harmonics" (2016, 23 citations), addresses a critical gap in the field: while autonomous cars have achieved impressive localisation, small, rapidly manoeuvring platforms—such as drones or legged robots—struggle with traditional visual methods under dynamic lighting and motion blur. Stone’s key contribution is a novel skyline-based approach that leverages ultraviolet sensors and spherical harmonic representations to achieve reliable place recognition even during aggressive manoeuvres. This work demonstrates how bio-inspired sensing and mathematical modelling can overcome the limitations of conventional cameras in outdoor, unstructured settings. With 23 citations, the paper has influenced subsequent research in robust robot navigation, particularly for search-and-rescue and field robotics. Stone’s research highlights the importance of designing perception systems that match the physical capabilities of modern, highly dynamic robots, making him a notable figure in the intersection of computer vision, sensor design, and field robotics.
Research Focus
Key Achievements
Top Papers
- 1