【摘 要】
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In this paper, a comparative study of the path plan-ning problem using evolutionary algorithms, in comparison with classical methods such as the A8 algorithm, is presented for a holonomic mobile robot. The configured navigation system, which consists of t
【机 构】
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Department of System Engineering,école de Technologie Supérieure,Montreal QC H3C 1K3,Canada
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In this paper, a comparative study of the path plan-ning problem using evolutionary algorithms, in comparison with classical methods such as the A8 algorithm, is presented for a holonomic mobile robot. The configured navigation system, which consists of the integration of sensors sources, map formatting, global and local path planners, and the base control-ler, aims to enable the robot to follow the shortest smooth path delicately. Grid-based mapping is used for scoring paths effi-ciently, allowing the determination of collision-free trajectories from the initial to the target position. This work considers the evolutionary algorithms, the mutated cuckoo optimization al-gorithm (MCOA) and the genetic algorithm (GA), as a global planner to find the shortest safe path among others. A non-uni-form motion coefficient is introduced for MCOA in order to in-crease the performance of this algorithm. A series of experi-ments are accomplished and analyzed to confirm the perform-ance of the global planner implemented on a holonomic mobile robot. The results of the experiments show the capacity of the planner framework with respect to the path planning problem under various obstacle layouts.
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