Simulated annealing: theory and applications
Simulated annealing: theory and applications
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms and Simulated Annealing
Genetic Algorithms and Simulated Annealing
Motion coordination for industrial robotic systems with redundant degrees of freedom
Robotics and Computer-Integrated Manufacturing
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In this paper we consider the problem of coordinating multiple motion devices for welding. We focus on the problem of coordinating a three-axis positioning table and a six-axis manipulator. The problem is complex as there are nine axes involved and a number of permutations are possible which achieve the same movements of the weld torch. The system is redundant and the robot has singular configurations. As a result, manual programming of the robot system is rather difficult to complete.Our approach to the coordination problem is based on a subdivision of tasks. The welding table is coordinated to align the weld point surface to be anti-parallel to the gravity direction. The six-axis robot is constrained to move the weld torch along the weld trajectory. Robot coordination is achieved by placing the positioning table in a good maneuverability position, i.e. far from its singular configurations and far from the motion limits of the six-axis arm and the motion limits of the track. While considering multiple criteria, including the welding orientation, a Genetic Algorithm was employed to globally optimize six relevant redundant degrees of the multiple robotic system for welding. The joint angles of the arm were generated by inverse kinematics. Our method of redundancy coordination is superior to pseudo-inverse techniques, for it is more global and accurate.