An L?-Norm Based Optimization Method for Sparse Redundancy Resolution of Robotic Manipulators

نویسندگان

چکیده

For targeted motion control tasks of manipulators, it is frequently necessary to make use full levels joint actuation guarantee successful planning and path tracking. Such way may keep the in a non-sparse manner during process. In order improve sparsity for manipulator systems, novel scheme which can optimally sparsely adopt proposed this brief. The strategy formulated as constrained $L_{1}$ norm optimization problem, an equivalent enhanced solution dealing with bounded velocity well. A new primal dual neural network set division further applied solve such control. Simulation experiment results demonstrate efficiency, accuracy superiority method adopting actuation. average (i.e., - notation="LaTeX">$\|\dot \theta \|_{p}$ where notation="LaTeX">$\theta $ denotes angle) be increased by 39.22% 51.30% tracking notation="LaTeX">$X Y$ Z$ planes respectively, indicating that enhanced.

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ژورنال

عنوان ژورنال: IEEE Transactions on Circuits and Systems Ii-express Briefs

سال: 2022

ISSN: ['1549-7747', '1558-3791']

DOI: https://doi.org/10.1109/tcsii.2021.3088942