Title :
Multirobot Forest Coverage for Weighted and Unweighted Terrain
Author :
Zheng, Xiaoming ; Koenig, Sven ; Kempe, David ; Jain, Sonal
Author_Institution :
Comput. Sci. Dept., Univ. of Southern California, Los Angeles, CA, USA
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 polynomial-time 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.
Keywords :
forestry; mobile robots; optimisation; polynomials; MFC; NP-hard problems; lawn mowing; mobile robots; multiple robots; multirobot coverage problems; multirobot forest coverage; polynomial time constant factor approximation algorithms; unweighted terrain; weighted terrain; Algorithm design and analysis; Approximation algorithms; Approximation methods; Polynomials; Robot sensing systems; Terrain factors; Approximation algorithm; NP-hardness; cell decomposition; complexity; multirobot coverage; robot teams; spanning tree coverage (STC); terrain coverage; tree cover;
Journal_Title :
Robotics, IEEE Transactions on
DOI :
10.1109/TRO.2010.2072271