Motion Planning of Robot Manipulator Based on Improved NSGA-II

被引：24
|
作者：
Huang, Ying [1 ,2 ]
Fei, Minrui [1 ]
机构：
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Yanchang Rd 149, Shanghai 200072, Peoples R China
[2] DianJi Univ, Elect Sch, Ganlan Rd 1350, Shanghai 201306, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2018年 / 16卷 / 04期
关键词：
Crowding distance; joint jerk; manipulator; non-dominated sorting; NSGA-II; Pareto; MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS; OPTIMIZATION; SYSTEMS;
D O I：
10.1007/s12555-016-0693-3
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the trajectory of a robot manipulator is planned using the non-dominated sorting genetic algorithm II (NSGA-II). Moreover, consumed time, Cartesian trajectory length, and smooth movement are used as the multi-objective to be optimized [1, 2]. The Pareto optimal solution set is obtained through NSGA-II, and simulation is used to obtain and verify the results. In an actual engineering case, the optimal solution of the Pareto solution set can be selected as the optimal path of a robot manipulator. Results show that the relationship between consumed time and joint jerk is a priority solution to practical engineering selection. Moreover, the spatial distribution of the optimal solution set is improved by enhancing the proposed crowding distance mechanism in the conventional NSGA-II algorithm.
引用
收藏
页码：1878 / 1886
页数：9
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