Papers
12
Total Citations
212
H-Index
9
About
Bruno Damas is a roboticist whose research lies at the intersection of motion planning, robot learning, and autonomous manipulation. He is best known for introducing the "forbidden velocity map" (2009, 45 citations), a seminal method for real-time obstacle avoidance in dense, cluttered environments that has become a foundational reference in safe robot navigation. Damas has also made significant contributions to robot learning from demonstration, notably developing deep neural network approaches that enable robots to learn complex household tasks like table-cleaning from kinesthetic demonstrations (2018, 29 and 16 citations). His work on incremental learning of dynamic models and context-dependent kinematics (2014, 28 citations) addresses the critical challenge of robots adapting to changing tools and environments through online learning, without requiring precomputed analytical models. Across his career, Damas has advanced both the theoretical foundations and practical applications of autonomous robotics, from robotic soccer dribbling (2003) to multi-robot adversarial games (2004). His research consistently emphasizes autonomy, adaptability, and real-world deployment, making his contributions valuable for students and researchers working on service robots, humanoid control, and intelligent navigation systems.
Research Focus
Key Achievements
Top Papers
- 1Avoiding moving obstacles: the forbidden velocity map45 citations · 2009
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- 7A learning framework for generic sensory-motor maps13 citations · 2007
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- 9Online learning of humanoid robot kinematics under switching tools contexts10 citations · 2013
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