Multirobot forest coverage for weighted and unweighted terrain

  • Authors:

  • Xiaoming Zheng;Sven Koenig;David Kempe;Sonal Jain

  • Affiliations:

  • Computer Science Department, University of Southern California, Los Angeles, CA;Computer Science Department, University of Southern California, Los Angeles, CA;Computer Science Department, University of Southern California, Los Angeles, CA;Microsoft, Redmond, WA

  • Venue:
  • IEEE Transactions on Robotics
  • Year:
  • 2010

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Abstract

One of the main applications of mobile robots is coverage: visiting each location in known terrain. Coverage is crucial for lawn mowing, cleaning, harvesting, search-and-rescue, intrusion detection, and mine clearing. Naturally, coverage can be sped up with multiple robots. However, we show that solving several versions of multirobot coverage problems with minimal cover times is NP-hard, which provides motivation for designing polynomialtime constant-factor approximation algorithms. We then describe multirobot forest coverage (MFC), a new polynomial-time multirobot coverage algorithm based on an algorithm by Even et al. [Min-max tree covers of graphs. Oper. Res. Lett., vol. 32, pp. 309- 315, 2004] for finding a tree cover with trees of balanced weights. Our theoretical results show that the cover times of MFC in weighted and unweighted terrain are at most about a factor of 16 larger than minimal. Our simulation results show that the cover times of MFC are close to minimal in all tested scenarios and smaller than the cover times of an alternative multirobot coverage algorithm.