Efficient Boustrophedon Multi-Robot Coverage: an algorithmic approach

Ioannis Rekleitis, Ai Peng New, Edward Samuel Rankin, Howie Choset
Annals of Mathematics and Artificial Intelligence
Apr. 2008
[140 citations]


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 cellbased 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.



  author       = {Ioannis Rekleitis and Ai Peng New and Edward Samuel
		 Rankin and Howie Choset},
  title        = {Efficient Boustrophedon Multi-Robot Coverage: an
		 algorithmic approach},
  journal      = {Annals of Mathematics and Artificial Intelligence},
  year	       = {2008},
  volume       = {52},
  number       = {2-4},
  pages        = {109-142},
  month        = {Apr.}

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