Hybrid genetic algorithms for energy efficient path placement of a 6 dof robot manipulator
Abstract: The performance of a manipulator during the execution of a task depends, among other things, on the position of the task inside the robot’s working envelope. When a task can be performed in different locations, depending on the position chosen the solution to the inverse kinematics problem will be different. Thus, by judiciously placing the robot and the given path in the workstation, it is possible to improve its behavior. This project deals with the optimal path placementin order to reduce the overall energy consumption for a 6-dof industrial manipulator. A framework for the visualization of the consumption in the working envelope is proposed and described. Genetic algorithms (GA) are chosen to solve the optimization problem, and the advantages they bring are also described. The proposed approach tries to merge the GA approach with a "brute-force" solution, which is also described. Finally, the goodness of the framework is assessed by comparison of the result with simulations performed with RobotStudioTM.
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