Dynamic Distributed PSO joints elites in Multiple Robot Path Planning Systems: theoretical and practical review of new ideas

Path planning problem for large number of robots is a quite challenging problem in mobile robotics since their control and coordination becomes unreliable and sometimes unfeasible. Particle Swarm Optimization (PSO) has been demonstrated to be a useful technique in the field of robotic research. This paper discusses an optimal path planning algorithm based on a Dynamic Distributed Particle Swarm Optimization Algorithm (DPSO). The purpose of this approach is to find collision free optimal paths using two local optima detectors. This would add diversity to the population and hence avoid stagnation problem. The results show that the DPSO has a better ability to get away from local optimums than the distributed PSO (dPSO). Simulations prove that this methodology is effective for every robot in multi-robot framework to discover its own proper path from the start to the destination position with minimum distance and no collision with obstacles. © 2016 The Authors. Published by Elsevier B.V. Peer-review under responsibility of KES International.

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