Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach

  • Authors:

  • Ioannis Rekleitis;Ai Peng New;Edward Samuel Rankin;Howie Choset

  • Affiliations:

  • School of Computer Science, McGill University, Montreal, Canada;DSO National Laboratories, Singapore, Singapore;DSO National Laboratories, Singapore, Singapore;Robotics Institute, Carnegie Mellon University, Pittsburgh, USA

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

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.