现代制造工程 ›› 2018, Vol. 456 ›› Issue (9): 70-75.doi: 10.16731/j.cnki.1671-3133.2018.09.014

• 机器人技术 • 上一篇    下一篇

移动式煤炭采样机采样臂智能避障路径规划方法研究

付兴1, 徐海波1, 王军2, 白志东1, 李和薇1   

  1. 1 西安交通大学机械工程学院,西安 710049;
    2 西安红宇矿用特种移动设备有限公司,西安 710075
  • 收稿日期:2017-05-01 出版日期:2018-09-20 发布日期:2018-09-27
  • 作者简介:付兴,硕士研究生,研究方向为工业机器人与控制。徐海波,通信作者,工学博士,教授,研究方向为工业机器人,机械电子工程。E-mail:fuxing@stu.xjtu.edu.cn
  • 基金资助:
    陕西省科技统筹创新工程计划项目(2015KTCQ01-26)

Research on intelligent obstacle avoidance path planning method for sampling arm of mobile coal sampler

Fu Xing1, Xu Haibo1, Wang Jun2, Bai Zhidong1, Li Hewei1   

  1. 1 School of Mechanical Engineering,Xi’an Jiaotong University,Xi’an 710049,China;
    2 Xi’an Hongyu Mine Special Mobile Equipment Limited Corporation,Xi’an 710075,China
  • Received:2017-05-01 Online:2018-09-20 Published:2018-09-27

摘要: 针对煤炭采样臂智能避障路径规划问题,基于改进人工势场算法提出了一种路径规划方法。根据采样臂工作特点,构建了一种位姿信息的表征方法,并建立了采样臂与障碍间的虚拟仿真模型。以采样臂关节空间为搜索空间,以总势能最小为目标函数,实现了避障路径规划。规划过程综合考虑了关节限位、连杆碰撞与障碍物安全距离信息,并通过引入虚拟坡度防止规划陷入局部极小值。通过仿真实验得到的路径平滑连续,且满足安全距离的要求,验证了规划方法的有效性和可行性。

关键词: 人工势场法, 路径规划, 避障控制, 采样臂

Abstract: Propose a path planning method based on improving artificial potential field,aiming at solving the problem of intelligent obstacle avoidance path planning for coal sampling arm.According to the working characteristics of the sampling arm,a kind of characterization method of pose information is constructed,and a virtual simulation model between sampling arm and obstacle is established.Taking the sampling arm joint space as the search space,and the minimum potential energy as the objective function,the obstacle avoidance path planning is realized by improving the artificial potential field method.The joint limit,link collision and obstacle safety distance information were taken into account for the planning process.The algorithm sets a virtual slope to prevent planning from falling into local minimum.At last,the validity and feasibility of the proposed method are verified by simulation experiments.

Key words: artificial potential field, path planning, obstacle avoidance control, sampling arm

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