A Sampling-Based Motion Assignment Strategy with Multi-Performance Optimization for Macro-Micro Robotic System

This article proposes a sampling-based motion assign- ment strategy for coordinated motion planning of macro-micro robotic systems. It is used to achieve performance enhancements while solving joint trajectories. The sampling strategy is imple- mented by traversing a series of feasible sets generated by the trajectory constraints of the micro robot. Meanwhile, two kinds of performance index maps are introduced to achieve normalization and integration of multiple performance indices. They are used for iterative generation of trajectories and overall performance evaluation, respectively. Comparative numerical results prove the validity of the proposed strategy.