Path planning problem of mobile robot is one that has intrigued and has received much attention throughout the history of robotics, since it is at the essence of what a mobile robot needs to be considered truly “autonomous”. A mobile robot must be able to find collision-free paths to move from one location to another, and in order to truly show a level of intelligence these paths must be optimized under some criteria that are important to the robot, working space and given problem. In this paper we propose a new structured multi-objective genetic algorithm to solve this problem. In our method we explore only valid search space that results in a smaller search space. Also we show the defect of earlier evaluation function and present a new evaluation function. To evaluate our idea we compare our evaluation function with other ones and show the performance of our method. Experiments show the ability of our method in finding best paths with low generation and population.
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