Thomas Moulard
Papers
1
Total Citations
2
H-Index
1
About
Thomas Moulard is a robotics researcher whose primary contributions lie in humanoid robot locomotion and motion planning, with a particular focus on collision-free navigation in cluttered environments. His most-cited work, "Collision-free walk planning for humanoid robots using numerical optimization" (2010, 2 citations), introduces a two-step algorithm that first plans a collision-free path for the robot's bounding box using classical path planning, then refines the trajectory through numerical optimization to ensure stable, feasible walking motions. This approach addresses the critical challenge of enabling humanoid robots to navigate real-world spaces safely and efficiently. Moulard's research bridges the gap between theoretical path planning and practical robotic implementation, offering solutions that consider both geometric constraints and dynamic stability. While his citation count is modest, his work contributes to the foundational understanding of how humanoid robots can move autonomously in complex environments, making him a notable figure in the specialized field of humanoid locomotion planning.
Research Focus
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Top Papers
- 1