Affiliations: Artificial Intelligence Laboratory, Dept. of
Electronics and Tele-Communication Engineering, Jadavpur University, Calcutta-
700 032, India | University of South Australia, Mawson Lakes Campus,
Adelaide, SA 5095, Australia | Department of Computer Science, University of
Missouri, St. Louis, MO 63121, USA
Abstract: This paper provides an alternative approach to the co-operative
multi-robot path planning problem using parallel differential evolution
algorithms. Both centralized and distributed realizations for multi-robot path
planning have been studied, and the performances of the methods have been
compared with respect to a few pre-defined yardsticks. The distributed approach
to this problem out-performs its centralized version for multi-robot planning.
Relative performance of the distributed version of the differential evolution
algorithm has been studied with varying numbers of robots and obstacles. The
distributed version of the algorithm is also compared with a PSO-based
realization, and the results are competitive.
