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Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach

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Abstract

This paper presents algorithmic solutions for the complete coverage path planning problem using a team of mobile robots. Multiple robots decrease the time to complete the coverage, but maximal efficiency is only achieved if the number of regions covered multiple times is minimized. A set of multi-robot coverage algorithms is presented that minimize repeat coverage. The algorithms use the same planar cell-based decomposition as the Boustrophedon single robot coverage algorithm, but provide extensions to handle how robots cover a single cell, and how robots are allocated among cells. Specifically, for the coverage task our choice of multi-robot policy strongly depends on the type of communication that exists between the robots. When the robots operate under the line-of-sight communication restriction, keeping them as a team helps to minimize repeat coverage. When communication between the robots is available without any restrictions, the robots are initially distributed through space, and each one is allocated a virtually-bounded area to cover. A greedy auction mechanism is used for task/cell allocation among the robots. Experimental results from different simulated and real environments that illustrate our approach for different communication conditions are presented.

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Authors and Affiliations

  1. School of Computer Science, McGill University, Montreal, Canada

    Ioannis Rekleitis

  2. DSO National Laboratories, Singapore, Singapore

    Ai Peng New & Edward Samuel Rankin

  3. Robotics Institute, Carnegie Mellon University, Pittsburgh, USA

    Howie Choset

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  1. Ioannis Rekleitis
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  2. Ai Peng New
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  3. Edward Samuel Rankin
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  4. Howie Choset
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Correspondence to Ioannis Rekleitis.

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Rekleitis, I., New, A.P., Rankin, E.S. et al. Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach. Ann Math Artif Intell 52, 109–142 (2008). https://doi.org/10.1007/s10472-009-9120-2

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