Improved shuffled frog Leaping Algorithm for Path Planning of multiple Mobile-Robot

Abstract

Improved shuffled frog leaping algorithm (ISFLA) has been proposed in this paper for multi-robot path planning in a clutter environment. Basic SFLA algorithm has been improved in the local search process by adding the weight and acceleration factor in the original version of SFLA to avoid the local optima and premature convergence. ISFLA technique has been embedded into the multi-robot system in a dynamic framework for generating optimal trajectory path by determining an optimal subsequent position for each robot from their existing position. Fitness function have been formulated by considering the different constraints and then, it optimized through ISFLA for generating optimal trajectory smooth path by avoiding the obstacles present in the environment. Finally, the simulation and experiment have been carried out to validate the performance of the proposed algorithm. The results obtained through ISFLA, SFLA and IGSA in terms of runtime, path deviation, the path travelled and energy utilized during travel shows ISFLA has outperformed its competitors.