Papers
7
Total Citations
433
H-Index
5
About
Tobias Kunz is a leading researcher in robot motion planning and control, with a focus on enabling robots to operate safely and efficiently in dynamic, human-centered environments. His work bridges the gap between theoretical planning algorithms and practical real-time implementation. Kunz is perhaps best known for his foundational contributions to the DART (Dynamic Animation and Robotics Toolkit) physics engine, a widely-used open-source library for simulating rigid-body dynamics. The key paper on DART has garnered over 270 citations, underscoring its critical role in robotics research and education. He has also made significant advances in real-time path planning for articulated manipulators, developing strategies that integrate probabilistic roadmaps with 3D sensor data to allow robots like Care-O-Bot 3 to react to changing surroundings. His work on acceleration-limited kinodynamic planning provides a computationally efficient middle ground between geometric and full-dynamics planning, and his innovative "robot limbo" controller demonstrates how dynamically stable robots can navigate under low obstacles. Through these contributions, Kunz has helped make complex motion planning both theoretically sound and practically deployable.
Research Focus
Key Achievements
Top Papers
- 1DART: Dynamic Animation and Robotics Toolkit272 citations · 2018
- 2Real-time path planning for a robot arm in changing environments64 citations · 2010
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- 5Turning Paths Into Trajectories Using Parabolic Blends10 citations · 2011
- 6Dynamic chess: Strategic planning for robot motion5 citations · 2011
- 7Real-Time Motion Planning for a Robot Arm in Dynamic Environments2 citations · 2009