Zhiwei Lin1, Hui Wang1,*, Tianding Chen1, Yingtao Jiang2, Jianmei Jiang3, Yingpin Chen1
CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1357-1379, 2024, DOI:10.32604/cmes.2023.045990
Abstract In the domain of autonomous industrial manipulators, precise positioning and appropriate posture selection in path planning are pivotal for tasks involving obstacle avoidance, such as handling, heat sealing, and stacking. While Multi-Degree-of-Freedom (MDOF) manipulators offer kinematic redundancy, aiding in the derivation of optimal inverse kinematic solutions to meet position and posture requisites, their path planning entails intricate multi-objective optimization, encompassing path, posture, and joint motion optimization. Achieving satisfactory results in practical scenarios remains challenging. In response, this study introduces a novel Reverse Path Planning (RPP) methodology tailored for industrial manipulators. The approach commences by conceptualizing the manipulator’s end-effector as an… More >
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