Online Time-Optimal Trajectory Planning for Robotic Manipulators Using Adaptive Elite Genetic Algorithm With Singularity Avoidance | Zendy

Yi Liu | Zendy; Chen Guo | Zendy; Yongpeng Weng | Zendy

Open Access

Online Time-Optimal Trajectory Planning for Robotic Manipulators Using Adaptive Elite Genetic Algorithm With Singularity Avoidance

Author(s) -

Yi Liu,

Chen Guo,

Yongpeng Weng

Publication year - 2019

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2019.2945824

Subject(s) - singularity , trajectory , genetic algorithm , quintic function , control theory (sociology) , gravitational singularity , computer science , mathematical optimization , robot , trajectory optimization , mathematics , algorithm , artificial intelligence , optimal control , nonlinear system , mathematical analysis , physics , control (management) , astronomy , quantum mechanics

In this paper, a new method of online planning high smooth and time-optimal trajectory for robotic manipulators that applies an adaptive elite genetic algorithm with singularity avoidance (AEGA-SA) is presented. The strategy is designed as a combination of the time-optimal trajectory planning with quintic polynomial in Cartesian space. For improving optimization performance, elitist group and adaptive adjustment mechanisms are used based on genetic algorithm (GA) framework. In the meantime, GA is combined with singularity avoidance mechanism to avoid the singularities appearing in the trajectory, improves the recognition capability of optimum solution. Experimental results show that, the proposed approach is more effective and better performance than the original GA and its variants, with ensuring a both smooth and efficiency performance for the robotic manipulators.

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