Papers
4
Total Citations
48
H-Index
3
About
Antoine Hoarau is a robotics researcher whose work lies at the intersection of safe human-robot interaction, skill learning, and whole-body control. His most influential contribution addresses the critical challenge of physical human-robot collaboration, where he developed energy-based control methods that ensure safety during contact—a foundational concern for bringing robots out of cages and into human environments (19 citations). Hoarau has also made significant strides in robot skill acquisition, pioneering approaches for the simultaneous discovery and improvement of reusable skill options, as well as learning compact parameterized skills from single regression models—work that enables robots to generalize learned behaviors to novel situations without requiring exhaustive demonstrations (27 combined citations). More recently, he contributed to the OCRA (Optimization-based Control for Robotics Applications) framework, a set of platform-independent libraries that streamline the implementation of hierarchical and whole-body controllers for platforms like the iCub humanoid. Hoarau’s research elegantly bridges the gap between theoretical control theory and practical robotic systems, offering concrete tools and methods that advance both the safety and adaptability of autonomous robots.
Research Focus
Key Achievements
Top Papers
- 1Energy Based Control for Safe Human-Robot Physical Interaction19 citations · 2017
- 2Simultaneous on-line Discovery and Improvement of Robotic Skill options14 citations · 2014
- 3Learning compact parameterized skills with a single regression13 citations · 2013
- 4