Papers
26
Total Citations
964
H-Index
13
About
Michael Otte is a leading researcher in robotics, with key contributions spanning motion planning, multi-robot coordination, and computer vision. His most impactful work is the development of RRT<sup>X</sup>, the first asymptotically optimal, single-query sampling-based replanning algorithm capable of operating in dynamic environments with unpredictable obstacles. This algorithm, detailed in his 2015 paper (225 citations), enables real-time motion replanning without prior offline computation, a breakthrough for autonomous systems in uncertain settings. Otte also pioneered auction-based methods for multi-robot task allocation in communication-limited environments, as seen in his 2019 paper (154 citations), which addresses the critical challenge of coordinating robots under harsh communication constraints. His earlier work includes advances in optical flow estimation (191 citations) and local path planning for unstructured environments. Otte’s research has been recognized through his role as an editor for the Distributed Autonomous Robotic Systems series and his contributions to real-time robotics. With over 800 total citations, his work continues to shape the fields of autonomous navigation and multi-robot systems, offering practical solutions for real-world deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2Optical flow estimation: Advances and comparisons191 citations · 1994
- 3Auctions for multi-robot task allocation in communication limited environments154 citations · 2019
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- 6Distributed Autonomous Robotic Systems41 citations · 2019
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