A Comparison of General-Purpose FOSS Compression Techniques for Efficient Communication in Cooperative Multi-Robot Tasks

Gonçalo S. Martins, David Portugal, Rui P. Rocha

2014

Abstract

The efficient sharing of information is a commonly overlooked problem in methods proposed for cooperative multi-robot tasks. However, in multi-robot scenarios, especially when the communication network’s quality of service is less than desirable, either in bandwidth or reliability, efficient information exchange is a key aspect for the successful deployment of coordinated robotic teams with proper exchange of information. Compression is a popular, well-studied solution for transmitting data through constrained communications channels, and many general-purpose solutions are available as free and open-source software (FOSS) projects. There are various benchmarking tools capable of comparing the performance of these techniques, but none that differentiate between them in the compression of the typical data exchanged among robots in a cooperative task. Thus, choosing a compression technique to be used in this context is still a challenge. In this paper, the issue of efficiently communicating data among robots is addressed by comparing the performance of various compression techniques in a case study of multi-robot simultaneous localization and mapping (SLAM) scenarios using occupancy grids, a cooperative task usually requiring the exchange of large amounts of data.

References

  1. Bermond, J.-C., Gargano, L., Perennes, S., Rescigno, A. A., and Vaccaro, U. (1996). Efficient collective communication in optical networks. In Automata, Languages and Programming, pages 574-585. Springer.
  2. Carpin, S. (2008). Fast and accurate map merging for multirobot systems. Autonomous Robots, 25(3):305-316.
  3. Cunningham, A., Paluri, M., and Dellaert, F. (2010). DDFSAM: Fully distributed SLAM using constrained factor graphs. In Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on, pages 3025-3030. IEEE.
  4. Deutsch, P. (1996). DEFLATE Compressed Data Format Specification version 1.3. RFC 1951 (Informational).
  5. Elfes, A. (1989). Using occupancy grids for mobile robot perception and navigation. Computer, 22(6):46-57.
  6. Ferreira, J. F., Castelo-Branco, M., and Dias, J. (2012). A hierarchical Bayesian framework for multimodal active perception. Adaptive Behavior, 20(3):172-190.
  7. Grisetti, G., Stachniss, C., and Burgard, W. (2007). Improved techniques for grid mapping with raoblackwellized particle filters. Robotics, IEEE Transactions on, 23(1):34-46.
  8. Huffman, D. A. et al. (1952). A method for the construction of minimum redundancy codes. Proceedings of the IRE, 40(9):1098-1101.
  9. Kümmerle, R., Steder, B., Dornhege, C., Ruhnke, M., Grisetti, G., Stachniss, C., and Kleiner, A. (2009). On measuring the accuracy of SLAM algorithms. Autonomous Robots, 27(4):387-407.
  10. Lazaro, M. T., Paz, L. M., Pinies, P., Castellanos, J. A., and Grisetti, G. (2013). Multi-robot SLAM using condensed measurements. In Proc. of 2013 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS 2013). IEEE.
  11. Pedrosa, E., Lau, N., and Pereira, A. (2013). Online SLAM Based on a Fast Scan-Matching Algorithm. In Progress in Artificial Intelligence, pages 295-306. Springer.
  12. Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., and Ng, A. Y. (2009). Ros: an open-source robot operating system. In ICRA workshop on open source software, volume 3.
  13. Rocha, R. P. (2006). Building Volumetric Maps with Cooperative Mobile Robots and Useful Information Sharing: a Distributed Control Approach Based on Entropy. PhD thesis, University of Porto, Portugal.
  14. Rocha, R. P., Portugal, D., Couceiro, M., Araujo, F., Menezes, P., and Lobo, J. (2013). The CHOPIN project: Cooperation between Human and rObotic teams in catastroPhic INcidents. In Safety, Security, and Rescue Robotics (SSRR), 2013 IEEE International Symposium on, pages 1-4. IEEE.
  15. Rodeh, O. and Teperman, A. (2003). zFS-a scalable distributed file system using object disks. In Mass Storage Systems and Technologies, 2003.(MSST 2003). Proceedings. 20th IEEE/11th NASA Goddard Conference on, pages 207-218. IEEE.
  16. Salomon, D. (2007). A concise introduction to data compression. Springer.
  17. Ziv, J. and Lempel, A. (1977). A universal algorithm for sequential data compression. IEEE Transactions on Information Theory, 23(3):337-343.
  18. Ziv, J. and Lempel, A. (1978). Compression of individual sequences via variable-rate coding. Information Theory, IEEE Transactions on, 24(5):530-536.
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Paper Citation


in Harvard Style

Martins G., Portugal D. and Rocha R. (2014). A Comparison of General-Purpose FOSS Compression Techniques for Efficient Communication in Cooperative Multi-Robot Tasks . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-040-6, pages 136-147. DOI: 10.5220/0005058601360147


in Bibtex Style

@conference{icinco14,
author={Gonçalo S. Martins and David Portugal and Rui P. Rocha},
title={A Comparison of General-Purpose FOSS Compression Techniques for Efficient Communication in Cooperative Multi-Robot Tasks},
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2014},
pages={136-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005058601360147},
isbn={978-989-758-040-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - A Comparison of General-Purpose FOSS Compression Techniques for Efficient Communication in Cooperative Multi-Robot Tasks
SN - 978-989-758-040-6
AU - Martins G.
AU - Portugal D.
AU - Rocha R.
PY - 2014
SP - 136
EP - 147
DO - 10.5220/0005058601360147