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Adaptive genetic algorithm for path planning of loosely coordinated multi-robot manipulators

高胜, Jie Zhao, 蔡鹤皋

发表年份
2003
引用次数
2

摘要

Adaptive genetic algorithm ASAGA, a novel algorithm, which can dynamically modify the parameters of Genetic Algorithms in terms of simulated annealing mechanism, is proposed for path planning of loosely coordinated multi-robot manipulators. Over the task space of a multi-robot, a strategy of decoupled planning is also applied to the evolutionary process, which enables a multi-robot to avoid falling into deadlock and calculating of composite C-space. Finally, two representative tests are given to validate ASA GA and the strategy of decoupled planning.

关键词

Motion planningGenetic algorithmRobotComputer scienceSimulated annealingRobot manipulatorDeadlockPath (computing)Mathematical optimizationArtificial intelligence

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