Cooperative Navigation Planning of Multiple Mobile Robots Using Improved Krill Herd

Robotics has been adequately utilized in different application areas due to its ability to work in a dynamic environment. The aim of finding a collision-free optimal path with minimum energy utilization is of prime concern in the present scenario. The current study presents an improvement of the classical krill herd (KH) in a new conceptual manner to address the multi-robot navigation problem in a clutter environment. The improved KH (IKH) involves tuning of influence parameters of basic KH to generate safe waypoints for each robot from their respective current positions to target by utilizing the herding behavior of krill swarm. The proposed algorithm mainly emphasizes maintaining a good balance between intensification and diversification. The results obtained from IKH have been compared with those acquired by KH and differential evolution (DE) in a similar environment to verify the effectiveness and robustness of the proposed algorithm. The error estimated for total navigation path traveled (TNPT) and average navigation path deviation (ANPD) between simulation and experimental investigation employing IKH is (9.68, 8.92) and reaches (12.42, 11.24) for KH and (15.03, 14.24) for DE. The outcome reveals that the proposed IKH algorithm is superior to KH and DE in terms of generating optimal and safe navigation path in simulation and experiments.