Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

Ting Wang, Zhijie Xin, Hongbin Miao, Huang Zhang, Zhenya Chen and Yunfei Du

Mathematical Problems in Engineering, 2020, vol. 2020, 1-8

Abstract:

Robot will be used in the grinding industry widely to liberate human beings from harsh environments. In the grinding process, optimal trajectory planning will not only improve the processing quality but also improve the machining efficiency. The aims of this study are to propose a new algorithm and verify its efficiency in achieving the optimal trajectory planning of the grinding robot. An objective function has been defined terms of both time and jerk. Improved whale optimization algorithm (IWOA) is proposed based on whale optimization algorithm (WOA) and differential evolution algorithm (DE). Mutation operation and selection operation of DE are imitated in the part of initialization to process the population initialized by WOA, and then, the search tasks of WOA are performed. Motion with a constant velocity of the end-effector is considered during fine grinding. The continuity of acceleration and velocity will be achieved by minimizing jerk, and at the same time, smooth robot movement can be obtained. Cubic spline interpolation is implemented. A six-axis industrial robot is used for this research. Results show that optimal trajectory planning based on IWOA is more efficient than others. This method presented in this paper may have some indirect significance in robot business.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3424313

DOI: 10.1155/2020/3424313

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