MULTI-ROBOT COVERAGE WITH DYNAMIC COVERAGE INFORMATION COMPRESSION

Zachary Wilson, Taylor Whipple, Prithviraj Dasgupta

Abstract

We consider the problem of distributed terrain or area coverage of an initially unknown environment using a set of mobile robots. We describe a distributed algorithm that is able to solve the distributed coverage problem without having each robot exchange its complete coverage map with other robots. The central part of our technique is a compression algorithm used by a robot to approximate the regions that have been previously covered and a fitness function that calculates the degree of accuracy of the approximated coverage information. The operation of our coverage algorithm is evaluated through experiments on simulated as well as physical Corobot robots. We have quantified the extent of overhead introduced by our coverage algorithm to prevent robots from performing repeated coverage. Overall, our results show that the robots are able to cover the environment within different environment settings while significantly reducing the amount of coverage information communicated between different robots.

References

  1. Batalin, M. and Sukhatme, G. (2002). Spreading out: A local approach to multi-robot coverage. In in Proc. of 6th International Symposium on Distributed Autonomous Robotic Systems, pages 373-382.
  2. Gabriely, Y. and Rimon, E. (2001). Spanning-tree based coverage of continuous areas by a mobile robot. Annals of Math and Artificial Intelligence, 31:77-98.
  3. Hazon, N. and Kaminka, G. (2008). On redundancy, efficiency, and robustness in coverage for multiple robots. Robotics and Auto. Systems, 56(12):1102-1114.
  4. Howard, A., Mataric, M., and Sukhatme, G. (2002). Mobile sensor network deployment using potential fields: A distributed, scalable solution to the area coverage problem. In in Proc. of 6th Int'l. Symp. on Distributed Autonomous Robotic Systems, pages 299-308.
  5. Perez, J. and Vidal, E. (1994). Optimum polygonal approximation of digitized curves. Pattern recognition letters, 15(8):743-750.
  6. Rutishauser, S., Correll, N., and Martinoli, A. (2009). Collaborative coverage using a swarm of networked miniature robots. Robotics and Auton Systems, 57(5):517-525.
  7. Salomon, D. (2006). Data Compression: The Complete Reference. Springer.
  8. Stachniss, C., Mozos, O., and Burgard, W. (2008). Efficient exploration of unknown indoor environments using a team of mobile robots. Annals of Mathematics and Artificial Intelligence, 52(2-4):205-227.
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Paper Citation


in Harvard Style

Wilson Z., Whipple T. and Dasgupta P. (2011). MULTI-ROBOT COVERAGE WITH DYNAMIC COVERAGE INFORMATION COMPRESSION . In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8425-75-1, pages 236-241. DOI: 10.5220/0003538202360241


in Bibtex Style

@conference{icinco11,
author={Zachary Wilson and Taylor Whipple and Prithviraj Dasgupta},
title={MULTI-ROBOT COVERAGE WITH DYNAMIC COVERAGE INFORMATION COMPRESSION},
booktitle={Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2011},
pages={236-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003538202360241},
isbn={978-989-8425-75-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - MULTI-ROBOT COVERAGE WITH DYNAMIC COVERAGE INFORMATION COMPRESSION
SN - 978-989-8425-75-1
AU - Wilson Z.
AU - Whipple T.
AU - Dasgupta P.
PY - 2011
SP - 236
EP - 241
DO - 10.5220/0003538202360241