New robot path planning optimization using hybrid GWO-PSO algorithm

Ayad Abdulrahem Alabdalbari, Issa Ahmed Abed


Actually, path planning is one of the most crucial aspects of mobile robots study. The primary goal of this research is to develop a solution to the path planning issues that occur when a “mobile robot” operates in a static environment. The problem is handled by finding a collision-free path that meets the given criteria for the shortest distance with quite the smoothness of the path. Two nature-inspired metaheuristic algorithms are used in the computation. By leading a hybrid “gray wolf optimization” with the “particle swarm optimization” (HGWO-PSO) computation that restricts the distance and follows path perfection guidelines, the primary shape is improved. In addition, simulation findings reveal that the proposed HGWO-PSO method is deeply serious in terms of path optimality when compared to path planning approaches such as group search optimizer GSO, PSO, artificial bee colony ABC, and GWO.


GWO; Optimization; Path planning; PSO; Robot

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