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Article type: Research Article
Authors: Hu, Yihuaa | Zhang, Shulinb | Chen, Yanhuic; *
Affiliations: [a] Engineering Training Centre, Guangxi University of Science and Technology, Liuzhou, Guangxi, China | [b] Department of Mechanical Engineering, Liuzhou Institute of Technology, Liuzhou, Guangxi, China | [c] School of Mechanical and Transportation Engineering, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
Correspondence: [*] Corresponding author: Yanhui Chen, School of Mechanical and Transportation Engineering, Guangxi University of Science and Technology, Liuzhou, Guangxi 545006, China. E-mail: yanhuichen2020@163.com.
Abstract: Robots are widely used in all walks of life, and their excellent work efficiency has been paid attention to. As the key component of robot, manipulator plays an important role in the running performance of robot. In order to effectively improve the trajectory accuracy and efficiency of the manipulator, a six degree of freedom (6-DOF) modular manipulator trajectory planning method based on polynomial interpolation is proposed, and its feasibility and effectiveness are verified by experiments. At the same time, the performance of the method is compared with two other methods of the same type. The experimental results show that the six degree of freedom modular trajectory planning method has a shorter running time, and the shortest running time is 1.62 s. Compared with the directions in previous studies, the planning trajectory of the proposed method is more practical and its accuracy is higher. In the iterative process, the running time of the proposed method is also the shortest. In addition, the minimum error of the three methods is about 1%, which is lower than the other two methods. It is concluded that the six degree of freedom modular trajectory planning method has high feasibility and performance, which is of great significance to improve the operating efficiency and stability of the robot.
Keywords: Polynomial interpolation, six degrees of freedom, manipulator, trajectory planning
DOI: 10.3233/JCM-226672
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 23, no. 3, pp. 1589-1600, 2023
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