Abstract
In this paper, we present a distributed information-gathering algorithm for multi-robot systems that use multiple path-based sensors to infer the locations of hazards within the environment. Path-based sensors output binary observations, reporting whether or not an event (like robot destruction) has occurred somewhere along a path, but without the ability to discern where along a path an event has occurred. Prior work has shown that path-based sensors can be used for search and rescue in hazardous communication-denied environments—sending robots into the environment one-at-a-time. We extend this idea to enable multiple robots to search the environment simultaneously. The search space contains targets (human survivors) amidst hazards that can destroy robots (triggering a path-based hazard sensor). We consider a case where communication from the unknown field is prohibited due to communication loss, jamming, or stealth. The search effort is distributed among multiple robots using an entropy-weighted Voronoi partitioning of the environment, such that during each search round all regions have approximately equal information entropy. In each round, every robot is assigned a region in which its search path is calculated. Numerical Monte Carlo simulations are used to compare this idea to other ways of using path-based sensors on multiple robots. The experiments show that dividing search effort using entropy-weighted Voronoi partitioning outperforms the other methods in terms of the information gathered and computational cost.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Otte, M., Sofge, D.: Path-based sensors: paths as Sensors, Bayesian updates, and Shannon information gathering. IEEE Trans. Autom. Sci. Eng. 18, 946–967 (2021)
Okabe, A., Boots, B., Sugihara, K.: Nearest neighbourhood operations with generalized Voronoi diagrams: a review. Int. J. Geogr. Inf. Syst. 8(1), 43–71 (1994)
Choset, H.: Coverage for robotics - a survey of recent results. Ann. Math. Artif. Intell. 31, 113–126 (2001)
Nair, V.G., Guruprasad, K.R.: GM-VPC: an algorithm for multi-robot coverage of known spaces using generalized Voronoi partition. Robotica 38(5), 845–860 (2020)
Jager, M., Nebel, B.: Dynamic decentralized area partitioning for cooperating cleaning robots. In: IEEE International Conference on Robotics and Automation, vol. 4, pp. 3577–3582 (2002)
Rankin, E.S., Rekleitis, I., New, A.P., Choset, H.: Efficient Boustrophedon multi-robot coverage: an algorithmic approach. Ann. Math. Artif. Intell. 52, 109–142 (2008)
Hazon, N., Kaminka, G.A.: On redundancy, efficiency, and robustness in coverage for multiple robots. Robot. Auton. Syst. 56, 1102–1114 (2008)
Agmon, N., Hazon, N., Kaminka, G.A.: The giving tree: constructing trees for efficient offline and online multi-robot coverage. Ann. Math. Artif. Intell. 52(2–4), 43–168 (2009)
Zheng, X., Koenig, S., Kempe, D., Jain, S.: Multirobot forest coverage for weighted and unweighted terrain. IEEE Trans. Rob. 26(6), 1018–1031 (2010)
Wilson, Z., Whipple, T., Dasgupta, P.: Multi-robot coverage with dynamic coverage information compression. In: International Conference on Informatics in Control, Automation and Robotics, pp. 236–241 (2011)
Michel, D., McIsaac, K.: New path planning scheme for complete coverage of mapped areas by single and multiple robots. In: IEEE International Conference on Mechatronics and Automation, pp. 1233–1240 (2012)
Macharet, D., Azpurua, H., Freitas, G., Campos, M.: Multi-robot coverage path planning using hexagonal segmentation for geophysical surveys. Robotica 36(8), 1144–1166 (2018)
Guruprasad, K.R., Wilson, Z., Dasgupta, P.: Complete coverage of an initially unknown environment by multiple robots using Voronoi partition. In: International Conference on Advances in Control and Optimization in Dynamical Systems, Bangalore, India (2012)
Kurabayashi, D., Ota, J., Arai, T., Yoshida, E.: Cooperative sweeping by multiple mobile robots. In: IEEE International Conference on Robotics and Automation, vol. 2, pp. 1744–1749 (1996)
Bhattacharya, S., Michael, N., Kumar, V.: Distributed coverage and exploration in unknown non-convex environments. In: Martinoli, A., et al. (eds.) Distributed Autonomous Robotic Systems. Springer Tracts in Advanced Robotics, vol. 83, pp. 61–75. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-32723-0_5
Otte, M., Sofge, D.: Path planning for information gathering with lethal hazards and no communication. In: International Workshop on the Algorithmic Foundations of Robotics, pp. 389–405 (2018)
Schwager, M., Dames, P., Rus, D., Kumar, V.: A multi-robot control policy for information gathering in the presence of unknown hazards. In: Christensen, H.I., Khatib, O. (eds.) Robotics Research. STAR, vol. 100, pp. 455–472. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-29363-9_26
Julian, B.J., Angermann, M., Schwager, M., Rus, D.: Distributed robotic sensor networks: an information-theoretic approach. Int. J. Robot. Res. 31(10), 1134–1154 (2012)
Dames, P., Schwager, M., Kumar, V., Rus, D.: A decentralized control policy for adaptive information gathering in hazardous environments. In: IEEE Conference on Decision and Control, pp. 2807–2813 (2012)
Dames, P., Schwager, M., Rus, D., Kumar, V.: Active magnetic anomaly detection using multiple micro aerial vehicles. IEEE Robot. Autom. Lett. 1, 153–160 (2016)
Acknowledgments
This study was conducted at the Motion and Teaming Laboratory, University of Maryland (UMD), and was funded by the Maryland Robotics Center (MRC) and the Office of Naval Research (ONR). Alkesh K. Srivastava and George P. Kontoudis were partially supported by the MRC to conduct this research with “Pathway to the Ph.D.” and “MRC Postdoctoral Fellowship” programs, respectively. This work has been possible with the support of ONR under the grant “Experimentally Verified Autonomous Path Planning for Information Gathering in Lethally Hostile Environments with Severely Limited Communication” (N0001420WX01827). The views, positions, and conclusions contained in this document are solely those of the authors and do not explicitly represent those of ONR.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Srivastava, A.K., Kontoudis, G.P., Sofge, D., Otte, M. (2024). Distributed Multi-robot Information Gathering Using Path-Based Sensors in Entropy-Weighted Voronoi Regions. In: Bourgeois, J., et al. Distributed Autonomous Robotic Systems. DARS 2022. Springer Proceedings in Advanced Robotics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-031-51497-5_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-51497-5_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-51496-8
Online ISBN: 978-3-031-51497-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)