Multi-robot Informative and Adaptive Planning for Persistent Environmental Monitoring

  • Kai-Chieh Ma
  • Zhibei Ma
  • Lantao Liu
  • Gaurav S. Sukhatme
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 6)


To gain a better understanding of environmental processes we are interested in the problem of deploying multi-robot systems for efficient collection of environmental data. For long-term autonomy, enabling persistent monitoring, it is important to consider the spatio-temporal variations of environmental phenomena. We develop a multi-robot persistent path planning method that reduces uncertainty in the environmental model. Our framework contains two components: the first component computes potential observation points that minimize model prediction uncertainty, and the second component uses this for online planning of multi-robot paths, while also taking into account the efficiency of information collection. We validated our method via simulations, and the results show that it produces multi-robot routing paths that are conflict-free, informative, and adaptive to the environmental dynamics.



The authors would like to thank Stephanie Kemna and Hordur Heidarsson for their valuable inputs on this paper.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Kai-Chieh Ma
    • 1
  • Zhibei Ma
    • 1
  • Lantao Liu
    • 1
  • Gaurav S. Sukhatme
    • 1
  1. 1.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA

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