Felix Burget
Brain (Germany), Sapienza University of Rome, University of Freiburg
Papers
7
Total Citations
373
H-Index
7
About
Felix Burget is a roboticist whose work sits at the intersection of humanoid whole-body control, autonomous manipulation, and accessible human-robot interaction. His most impactful contribution is a real-time imitation system for humanoids (167 citations), which enables robots to replicate complex human motions by focusing on key end-effector and center-of-mass trajectories—a foundational step toward fluid, human-like robot behavior. He has also advanced whole-body motion planning for articulated object manipulation (72 citations), tackling the challenge of maintaining balance while avoiding collisions during tasks like grasping. Burget’s research extends to assistive robotics, where he integrates deep-learning-based brain-computer interfaces with flexible goal formulation (49 citations). This work, including the "Acting Thoughts" project (23 citations), aims to give users with limited communication skills high-level control over service robots, bypassing traditional touch or speech interfaces. His inverse reachability maps (48 citations) further improve humanoid grasping by precomputing optimal stances. Collectively, Burget’s work—spanning motion planning, BCI, and task-level reasoning—demonstrates a commitment to making autonomous robots both capable and accessible, with applications from service assistance to inclusive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Real-time imitation of human whole-body motions by humanoids167 citations · 2014
- 2Whole-body motion planning for manipulation of articulated objects72 citations · 2013
- 3
- 4Stance selection for humanoid grasping tasks by inverse reachability maps48 citations · 2015
- 5
- 6Closed-Loop Robot Task Planning Based on Referring Expressions7 citations · 2018
- 7