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Cooperative multi-robot belief space planning for autonomous navigation in unknown environments

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Abstract

We investigate the problem of cooperative multi-robot planning in unknown environments, which is important in numerous applications in robotics. The research community has been actively developing belief space planning approaches that account for the different sources of uncertainty within planning, recently also considering uncertainty in the environment observed by planning time. We further advance the state of the art by reasoning about future observations of environments that are unknown at planning time. The key idea is to incorporate within the belief indirect multi-robot constraints that correspond to these future observations. Such a formulation facilitates a framework for active collaborative state estimation while operating in unknown environments. In particular, it can be used to identify best robot actions or trajectories among given candidates generated by existing motion planning approaches, or to refine nominal trajectories into locally optimal paths using direct trajectory optimization techniques. We demonstrate our approach in a multi-robot autonomous navigation scenario and consider its applicability for autonomous navigation in unknown obstacle-free and obstacle-populated environments. Results indicate that modeling future multi-robot interaction within the belief allows to determine robot actions (paths) that yield significantly improved estimation accuracy.

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Notes

  1. Optimality here refers to choosing the best actions from the given set of candidate paths.

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Acknowledgements

This work was partially supported by the Technion Autonomous Systems Program.

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  1. Department of Aerospace Engineering, Technion - Israel Institute of Technology, 32000, Haifa, Israel

    Vadim Indelman

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  1. Vadim Indelman
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Correspondence to Vadim Indelman.

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This is one of several papers published in Autonomous Robots comprising the Special Issue on Active Perception.

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Indelman, V. Cooperative multi-robot belief space planning for autonomous navigation in unknown environments. Auton Robot 42, 353–373 (2018). https://doi.org/10.1007/s10514-017-9620-6

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