A Dual-Thread Method for Time-Optimal Trajectory Planning in Joint Space Based on Improved NGA

Autor: Kaipeng Zhang, Ning Liu, Gao Wang
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Robotics, Vol 2020 (2020)
Druh dokumentu: article
ISSN: 1687-9600
1687-9619
DOI: 10.1155/2020/6859589
Popis: To solve the problem that the time-consuming optimization process of Genetic Algorithm (GA) can erode the expected time-saving brought by the algorithm, time-optimal trajectory planning based on cubic spline was used, after the modification to classical fitness sharing function of NGA, a dual-threaded method utilizing elite strategy characteristic was designed which was based on Niche Genetic Algorithm (NGA) with the fitness sharing technique. The simulation results show that the proposed method can mitigate the contradiction of the long term the optimization algorithm takes but a short running time the trajectory gets, demonstrating the effectiveness of the proposed method. Besides, the improved fitness sharing technique has reduced the subjective process of determining relevant parameters and the optimized trajectory results met performance constraints of the robot joints.
Databáze: Directory of Open Access Journals
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