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A novel algorithm, the immune genetic algorithm based on multi-agent, is proposed for the path planning of tightly coordinated two-robot manipulators, which constructs mainly immune operators accomplished by three steps: defining strategies and methods of multi-agent, calculating virtual forces acting on an agent, and constructing immune operators and performing immunization during the evolutionary process. It is illustrated to be able to restrain the degenerate phenomenon effectively and improve the searching ability with high converging speed.
A novel algorithm, the immune genetic algorithm based on multi-agent, is proposed for the path planning of tightly coordinated two-robot manipulators, which constructs mainly immune operators accomplished by three steps: defining strategies and methods of multi-agent, calculating virtual forces acting on an agent, and constructing immune operators and performing immunization during the evolutionary process. It is illustrated to be able to restrain the degenerate phenomenon effectively and improve the searching ability with high converging speed.