Abstract

In this paper, the adaptive simulated annealing genetic algorithm (ASAGA) is presented by integrating the advantages of adaptive mechanics, simulated annealing algorithm and simple genetic algorithm (SGA). More successful result is got in manipulator trajectory planning using ASAGA compared with simple genetic algorithm. The experiment results show that the method can be used in manipulator trajectory planning effectively and will shed new light on how to bring the redundancy into full play to improve the movement of manipulator

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