Papers
13
Total Citations
148
H-Index
6
About
Aymar de Rugy is a neuroscientist and robotics researcher whose work bridges human motor control, prosthetics, and human-robot interaction. His research spans two interconnected domains: understanding the biomechanical and neuromuscular foundations of natural human movement, and translating those insights into practical robotic and prosthetic control systems. Early in his career, de Rugy investigated how the nervous system coordinates multi-joint rhythmic arm movements, revealing how neuromuscular and biomechanical factors jointly determine solutions to motor redundancy. This foundational work informed his later engineering contributions, where he developed and evaluated intuitive control strategies for robotic prosthetic arms. His widely cited Reachy robotic arm platform (75 citations) has become a valuable testbed for the field, while his prosthesis control research demonstrated that amputees can reach naturally in virtual reality using movement-based strategies. More recently, de Rugy has advanced data-driven approaches to assistive robotics, releasing the publicly accessible 3D-ARM-Gaze dataset and developing gaze-driven action forecasting models to anticipate grasping intentions — work with significant implications for people with motor disabilities. His research consistently emphasizes biological plausibility as a design principle, demonstrating that robot postures mimicking human movement meaningfully improve operator control performance.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8FPGA-based SIFT implementation for wearable computing5 citations · 2019
- 9
- 10