A Hybrid Evolutionary Approach for Multi Robot Path Exploration Problem

Robot Path Exploration problem or Robot Motion planning problem is one of the famous problems in robot's offline decision making algorithms. In this paper, a hybrid approach is presented that combines clustering and Genetic Algorithm (GA) to solve the Multi Robot Path Exploration Problem. The aim is to find collision free path, which Robot can follow to reach the target from its starting position. Environment is considered as a complete weighted graph representing the locations or points in the world environment and Traveling Salesman Problem (TSP) solving approach, based on GA is tried to solve this problem. Clustering is used to group the points (land marks) in the environment and rendezvous point is selected where all the robots finally meet. Experimental results are presented to illustrate the performance of the proposed scheme.

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