Multi-robot path planning in a dynamic environment using improved gravitational search algorithm

• Published in: Journal of Electrical Systems and Information Technology Vol. 3; no. 2; pp. 295 - 313
• Main Authors: Das, P.K., Behera, H.S., Jena, P.K., Panigrahi, B.K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2016; SpringerOpen
• Subjects: Average path length; Average total trajectory path deviation; Average uncovered trajectory target distance; Gravitational search algorithm; Multi-robot path planning; Average uncovered trajectory target distance; Average total trajectory path deviation; Gravitational search algorithm; Average path length; Multi-robot path planning
• ISSN: 2314-7172; 2314-7172
• DOI: 10.1016/j.jesit.2015.12.003

This paper proposes a new methodology to optimize trajectory of the path for multi-robots using improved gravitational search algorithm (IGSA) in a dynamic environment. GSA is improved based on memory information, social, cognitive factor of PSO (particle swarm optimization) and then, population for next generation is decided by the greedy strategy. A path planning scheme has been developed using IGSA to optimally obtain the succeeding positions of the robots from the existing position. Finally, the analytical and experimental results of the multi-robot path planning have been compared with those obtained by IGSA, GSA and PSO in a similar environment. The simulation and the Khepera environmental results outperform IGSA as compared to GSA and PSO with respect to performance matrix.