Papers
21
Total Citations
519
H-Index
13
About
Thomas Flayols is a robotics researcher whose work spans humanoid robots, legged locomotion, and robot design optimization. He is perhaps best known for his contributions to the development of TALOS, a next-generation humanoid robot designed for industrial applications, a landmark paper that has garnered over 150 citations and helped define the capabilities expected of modern humanoid platforms. His research consistently addresses fundamental challenges in legged robotics, including state estimation, whole-body control, and locomotion over complex terrain. His 2017 work on floating-base estimators (52 citations) demonstrated practical, lightweight solutions critical for real-time humanoid control, while his contributions to the open-hardware quadruped Solo-12 showcased a commitment to accessible, reproducible robotics research. Flayols has embraced deep reinforcement learning as a tool for robust locomotion control, with recent work on constraint-aware RL policies and the Solo12 platform reflecting cutting-edge directions in the field. His contributions to computational co-design frameworks further highlight a systems-level perspective, optimizing robots concurrently for hardware and control efficiency. With over 420 cumulative citations across a decade of work, Flayols has established himself as an influential voice bridging theoretical foundations and practical deployment in legged robotics.
Research Focus
Key Achievements
Top Papers
- 1TALOS: A new humanoid research platform targeted for industrial applications150 citations · 2017
- 2Experimental evaluation of simple estimators for humanoid robots52 citations · 2017
- 3Controlling the Solo12 quadruped robot with deep reinforcement learning41 citations · 2023
- 4An Overview of Humanoid Robots Technologies40 citations · 2018
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- 10Simulation Aided Co-Design for Robust Robot Optimization17 citations · 2022