While the concepts of robotics and planning may be easily understood by the taking a single robot, it is not necessary that the problems we solve have a single robot in the planning scenario. In this chapter, the authors present systems with multiple robots, each robot attempts to coordinate and cooperate with the other robots for problem solving. The authors first look at the specific problems where multiple robots would be a boon for the system. This includes problems of maze solving, complete coverage, map building, and pursuit evasion. The inclusion of multiple robots in the scenario takes all the concepts of single robotic systems. It also introduces some new concepts and issues as well. They look into all these issues in the chapter which include optimality in terms of computational time and solution generated, completeness of planning, reaching a consensus, cooperation amongst multiple robots, and means of communication between robots for effective cooperation. These issues are highlighted by specific problems. The problems include multi-robot task allocation, robotic swarms, formation control with multiple robots, RoboCup, multi-robot path planning, and multi-robot area coverage and mapping. The authors specifically take the problem of multi-robot path planning, which is broadly classified under centralized and decentralized approaches. They discuss means by which algorithms for single robot path planning may be extended to the use of multiple robots. This is specifically done for the graph search, evolutionary, and behavioral approaches discussed in the earlier chapters of the book.
Decentralized Task and Path Planning for Multi-Robot Systems
