Coordination for Multi-Robot Exploration and Mapping

Abstract

This paper addresses the problem of exploration and mapping of an unknown environment by multiple robots. The mapping algorithm is an on-line approach to likelihood maximization that uses hill climbing to find maps that are maximally consistent with sensor data and odometry. The exploration algorithm explicitly coordinates the robots. It tries to maximize overall utility by minimizing the potential for overlap in information gain amongst the various robots. For both the exploration and mapping algorithms, most of the computations are distributed. The techniques have been tested extensively in real-world trials and simulations. The results demonstrate the performance improvements and robustness that accrue from our multirobot approach to exploration. 1

Cite

Text

Simmons et al. "Coordination for Multi-Robot Exploration and Mapping." AAAI Conference on Artificial Intelligence, 2000.

Markdown

[Simmons et al. "Coordination for Multi-Robot Exploration and Mapping." AAAI Conference on Artificial Intelligence, 2000.](https://mlanthology.org/aaai/2000/simmons2000aaai-coordination/)

BibTeX

@inproceedings{simmons2000aaai-coordination,
  title     = {{Coordination for Multi-Robot Exploration and Mapping}},
  author    = {Simmons, Reid G. and Apfelbaum, David and Burgard, Wolfram and Fox, Dieter and Moors, Mark and Thrun, Sebastian and Younes, Håkan L. S.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2000},
  pages     = {852-858},
  url       = {https://mlanthology.org/aaai/2000/simmons2000aaai-coordination/}
}