Recent Advances on Manipulator Trajectory Planning Methods

计算机科学 灵活性(工程) 自动化 弹道 平面图(考古学) 控制工程 约束(计算机辅助设计) 运动规划 机器人 移动机械手 工程类 人工智能 移动机器人 数学 物理 天文 考古 统计 历史 机械工程
作者
Hongxin Zhang,Hao-ran Qiu,Xu Zhang,Ping Hu
出处
期刊:Recent Patents on Mechanical Engineering [Bentham Science Publishers]
卷期号:13 (4): 303-327 被引量:6
标识
DOI:10.2174/2212797613666200319151513
摘要

Background: Traditional manipulator requires professionals to write control programs for specific job requirements so that the end-effector of the manipulator can work following the control instructions. However, the flexibility of the manipulator is not high under the control of off-line programming. With the diversification of the job requirements, the complexity of the work environment has gradually increased. Therefore, the relevant scholars focused their research on the automatic trajectory planning method of the manipulator. They used some algorithms to plan optimal trajectories for the manipulator to automatically avoid obstacles in the complex environment. Researches show that the hybrid optimal trajectory with parameter optimization such as time, energy and impact can be planned by automated programming under some constraint conditions. The trajectory planning is helpful to improve the automation and working efficiency of manipulators for the development of intelligent manufacturing. Objective: Providing references for researchers from related fields by reviewing recent advances of the manipulator trajectory planning. Methods: This paper reviews the latest patents and current representative articles related to the manipulator trajectory planning. The key methods of some references are introduced in several aspects of the algorithm, innovation and principle. Results: Researches on the manipulator trajectory planning in recent 10 years are reviewed. The differences between algorithms in latest patents and current articles are introduced and analyzed and the future developments and potential problems of the manipulator trajectory optimization are discussed. Conclusion: The manipulator trajectory planning reduces complicated operator and hard programming tasks, improving the intelligence of robots and the work efficiency. Current researches focus on collision- free, parameter-optimized and high-efficiency solution which can be used to solve the problem of the end-trajectory planning of the manipulator in the complicated space with obstacles. The aspects that need to be improved in the future include: algorithm reliability, operational security and intelligence, human-computer interaction, efficient simulation, and so on. More patents on manipulator trajectory planning should be invented.
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