A method for obtaining coordinated motion plans of manipulator robots is presented. This planning can be easily implemented by programs written in any industrial robot programming language, such as VAL II. The generated programs minimize the total motion time of the robots along their paths, with some constraints directed at avoiding collision between the robots. A method based on Evolution Strategies is used for the optimization.

A method based on the union of an Evolutionary Algorithm (EA) and a local search algorithm for obtaining coordinated motion plans of two manipulator robots is presented. A Decoupled Planning Approach has been used. For this purpose, the problem has been decomposed into two subproblems: path planning, where a collision-free path is found for each robot independently of the other, only considering fixed obstacles; and trajectory planning, where the paths are timed and synchronized in order to avoid collision with the other robot. This paper focuses on the second problem. A method is presented to minimize the total motion time of two manipulators along their paths, avoiding collision regardless of the accuracy of the dynamic model used. A hybrid technique with EA and local search methods has been implemented.

methods

/pdf/an-evolutionary-and-local-search-algorithm-for-planning-two-2xwqnmz63c.pdf

Coordinated Motion Planning Of Manipulators By Evolution Strategies

An Evolutionary and Local Search Algorithm for Planning Two Manipulators Motion

A method based on genetic algorithms for obtaining coordinated motion plans of manipulator robots is presented. A decoupled planning approach has been used; that is, the problem has been decomposed into two subproblems: path planning and trajectory planning. This paper focuses on the second problem. The generated plans minimize the total motion time of the robots along their paths. The optimization problem is solved by evolutionary algorithms using a variable-length individuals codification and specific genetic operators.

/pdf/using-genetic-algorithms-with-variable-length-individuals-1mnqxf8l0c.pdf

Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion

/pdf/coordinated-motion-planning-of-manipulators-by-evolution-1l4ocvqarm.pdf

Coordinated Motion Planning Of Manipulators By Evolution Strategies

Citations

An Evolutionary and Local Search Algorithm for Planning Two Manipulators Motion

Using Genetic Algorithms with Variable-length Individuals for Planning Two-Manipulators Motion

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