A Reciprocal Sampling Algorithm for Lightweight Distributed Multi-Robot Localization

This work is situated in the context of collaboratively solving the localization problem for unknown initial conditions. We address this problem with a novel, fully decentralized, real-time particle filter algorithm, designed to accommodate realistic robotic assumptions including noisy sensors, and asynchronous and lossy communication. In particular, we introduce a collaborative reciprocal sampling algorithm which allows a drastic reduction in the number of particles needed to achieve localization. We elaborate an analysis of our reciprocal sampling method and support our conclusions with simulation results. Finally, we validate our approach on a team of four real robots within a controlled experimental setup.

Published in:
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 3241-3247
Presented at:
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Fransisco, CA, USA, September 25-30, 2011
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa

 Record created 2011-07-17, last modified 2018-03-17

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