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Journal of Robotics
Volume 2018, Article ID 2571243, 7 pages
https://doi.org/10.1155/2018/2571243
Research Article

Adaptive Neuro-Fuzzy Inference System Based Path Planning for Excavator Arm

Hanoi University of Science and Technology, Vietnam

Correspondence should be addressed to Nga Thi-Thuy Vu; nv.ude.tsuh@yuhtihtuv.agn

Received 21 August 2018; Revised 8 November 2018; Accepted 19 November 2018; Published 2 December 2018

Academic Editor: Huosheng Hu

Copyright © 2018 Nga Thi-Thuy Vu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper presents a scheme based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to generate trajectory for excavator arm. Firstly, the trajectory is predesigned with some specific points in the work space to meet the requirements about the shape. Next, the inverse kinematic is used and optimization problems are solved to generate the via-points in the joint space. These via-points are used as training set for ANFIS to synthesis the smooth curve. In this scheme, the outcome trajectory satisfies the requirements about both shape and optimization problems. Moreover, the algorithm is simple in calculation as the numbers of via-points are large. Finally, the simulation is done for two cases to test the effect of ANFIS structure on the generated trajectory. The simulation results demonstrate that, by using suitable structure of ANFIS, the proposed scheme can build the smooth trajectory which has the good matching with desired trajectory even that the desired trajectory has the complicated shape.