Papers
7
Total Citations
388
H-Index
6
About
Sebastian Klemm is a leading researcher in robot motion planning and autonomous navigation, with a focus on developing algorithms that are both asymptotically optimal and computationally efficient. His most influential work, the RRT*-Connect algorithm (201 citations), combines the rapid solution-finding of RRT-Connect with the asymptotic optimality of RRT*, creating a powerful single-query planner that outperforms both predecessors. Beyond path planning, Klemm has pioneered the use of Graphics Processing Units (GPUs) for robotics, introducing a unified framework for voxel-based collision detection that dramatically accelerates planning in complex environments (65 citations). This GPU-centric approach extends to predictive collision detection for human-robot collaboration (27 citations) and online grasp planning using in-hand sensors. His applied work includes autonomous navigation for reconfigurable snake-like robots in challenging terrain and a complete multi-story valet parking system for electric vehicles, demonstrating his ability to bridge theoretical advances with real-world deployment. Klemm’s research has been recognized for its impact on both mobile manipulation and autonomous driving, with his multi-resolution 3D environment model also contributing to planetary exploration missions.
Research Focus
Key Achievements
Top Papers
- 1RRT*-Connect: Faster, asymptotically optimal motion planning201 citations · 2015
- 2Unified GPU voxel collision detection for mobile manipulation planning65 citations · 2014
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- 4Autonomous multi-story navigation for valet parking29 citations · 2016
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