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Manipulator multi-objective motion optimization control for high voltage power cable mobile operation robot

  • Wei JiangEmail author
  • Gongping Wu
  • Lianqing Yu
  • Hongjun Li
  • Wei ChenEmail author
Original Research

Abstract

In respond to the problem of the manipulator point to point motion planning of power cable mobile operation robot, a trajectory planning method based on joint motion time standardization combined with time contraction factor is proposed in this paper, the joint motion time is selected as an evaluation parameter of joint trajectory performance, and corresponding, the mapping relationship between trajectory performance and different joint motion time is also studied. Based on the research result and combined with the robot kinetics model, a mixing constraint control method of joint position, velocity and acceleration is proposed so as to realize the continuous, smooth, stable and non-collision obstacle avoidance motion optimization under the condition of joint global state constraints during manipulator operation motion. Compared with the traditional algorithm, the improved algorithm has achieved excellent trajectory performance under the premise of ensuring the safety manipulator motion, and this method can also avoid the occurrence of joint motion overshoot, which not only improve the efficiency of joint space motion but also reduce the energy consumption. Finally, the feasibility and effectiveness of the proposed algorithm are verified through simulation experiments and the engineering practicality of the proposed algorithm is verified by the field operation experiments.

Keywords

Mobile operation robot Multi-Objective Motion time Joint motion overshoot Optimization control 

Notes

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: this work was supported by National Natural Science Foundation of China (51275363), Natural Science Foundation of Hubei province (2018CFB273).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechanical Engineering and AutomationWuhan Textile UniversityWuhanChina
  2. 2.Hubei Engineering of Industrial Detonator Intelligent Assembly Research CenterWuhanChina
  3. 3.College of Power and Mechanical EngineeringWuhan UniversityWuhanChina

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