Felix Sygulla
Papers
20
Total Citations
228
H-Index
9
About
Felix Sygulla is a robotics researcher whose work sits at the intersection of humanoid locomotion, autonomous navigation, and real-time motion planning. His research has made significant contributions to enabling bipedal robots to operate safely and efficiently in complex, unknown environments — one of the most demanding frontiers in modern robotics. Sygulla is perhaps best known for his pioneering work on real-time path planning and obstacle avoidance for humanoid robots. His 2017 paper on autonomous navigation in dynamic environments has garnered 42 citations, establishing him as a key voice in making humanoid platforms competitive with conventional mobile robots. Complementing this, his vision-based 3D environment modeling work (21 citations) and fast object approximation systems (19 citations) form a cohesive framework for robust perception and planning under real-world constraints. Beyond navigation, Sygulla has contributed meaningfully to bipedal walking stabilization using model-based predictive control, kinematic optimization, and spline-based pattern generation. His hardware contributions are equally notable, including the development of a flexible low-cost tactile sensor and upgrades to the humanoid robot LOLA for dynamic multi-contact locomotion. With over 170 cumulative citations, his body of work reflects a researcher dedicated to bridging the gap between laboratory robotics and real-world autonomy.
Research Focus
Key Achievements
Top Papers
- 1Real-Time Path Planning in Unknown Environments for Bipedal Robots42 citations · 2017
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- 5A flexible and low-cost tactile sensor for robotic applications17 citations · 2017
- 6Model-based predictive bipedal walking stabilization15 citations · 2016
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