工业工程 ›› 2017, Vol. 20 ›› Issue (2): 56-63.doi: 10.3969/j.issn.1007-7375.e17-2002

• 实践与应用 • 上一篇    下一篇

RRT与人工势场法结合的机械臂避障规划

何兆楚, 何元烈, 曾碧   

  1. 广东工业大学 计算机学院, 广东 广州 510006
  • 收稿日期:2017-01-05 出版日期:2017-04-30 发布日期:2017-05-13
  • 作者简介:何兆楚(1990-),男,广东省人,硕士研究生,主要研究方向为智能机器人.
  • 基金资助:
    广东省应用型科技研发专项资金资助项目(2015B090922012);东莞产学研合作成果转化资助项目(2015509109107)

Obstacle Avoidence Path Planning for Robot Arm Based on Mixed Algorithm of Artificial Potential Field Method and RRT

HE Zhaochu, HE Yuanlie, ZENG Bi   

  1. School of Computer, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2017-01-05 Online:2017-04-30 Published:2017-05-13

摘要: 针对人工势场法在工业机械臂避障路径规划中容易陷入局部极小值的缺陷,利用改进的快速扩展随机树(rapidly-exploring random tree,RRT)算法与人工势场法结合进行避障路径规划。首先,利用人工势场法进行局部路径规划,当陷入局部极小值时,使用改进的快速扩展随机算法自适应地选择临时目标点,使搜索过程跳出局部极小值点;当机械臂逃离局部极小值点时,切换回人工势场法进行规划。该算法不仅能够实现工业机械臂末端执行器的避障,同时能够防止杆端与障碍物产生碰撞,最终到达目标点。仿真实验表明,该方法实现简单,能够适应环境的变化,在复杂的环境下依然有效,满足机械臂避障的要求。最后,通过进行实际实验表明了实际与仿真实验的一致性。

关键词: 人工势场法, 快速扩展随机树, 工业机械臂, 避障, 路径规划

Abstract: To solve the problem of artificial potential field algorithm being liable to fall into local minimum in the obstacle avoidance path planning of industrial robot arm, a combination of artificial potential field and improved Rapidly-exploring Random Tree (RRT) algorithm is applied. Firstly, artificial potential field algorithm is used in local obstacle avoidance path planning. When falling into local minimum, the improved RRT algorithm can adaptively select the temporary target point and make the search process jump out of the local minimum point. In addition, artificial potential field algorithm will be applied when the robot arm leaves the local minimum. This method not only achieves obstacle avoidance on the end effector of the robot arm, but also prevents the collision between the rod and the obstacle, eventually bringing the end effector to the target point. The simulation experiments show that the proposed method is simple and can adapt to the change of environment and is still effective in complex environment.The algorithm can satisfy the requirement of the obstacle avoidance of the robot arm. Finally, the experimental results show the consistency between the actual and the simulation results.

Key words: artificial potential field method, rapidly-exploring random tree, industrial robot arm, obstacle avoidance, path planning

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