Path plan of 6-DOF robot manipulators in obstacle environment based on navigation potential function

被引：0
作者：
Key Laboratory of Intelligent Control and Decision for Complex System, School of Automation, Beijing Institute of Technology, Beijing [1 ]
100081, China
机构：
[1] Key Laboratory of Intelligent Control and Decision for Complex System, School of Automation, Beijing Institute of Technology, Beijing
来源：
Beijing Ligong Daxue Xuebao | / 2卷 / 186-191期
关键词：
Artificial potential field; Collision avoidance; Manipulator; Navigation potential function; OpenGL; Path planning;
D O I：
10.15918/j.tbit1001-0645.2015.02.015
中图分类号：
学科分类号：
摘要：
Based on the navigation potential function, the path planning problem was studied for the MOTOMAN MH6 robot manipulator. According to the geometric features of the manipulator, the simplified model can be obtained. And by the method of sphere enveloping and analyzing the collision condition between the manipulator and obstacles, the free space of the manipulator was computed. The local minima points except goal were eliminated in advance by navigation potential function which can make the path arrive the goal, and the problem of local minima in traditional potential method was also be solved. The problem of selecting the value for the control parameter of the navigation function was explained by numerical simulation. The effectiveness and feasibility of the method is also validated in the virtual platform based on OpenGL. ©, 2015, Beijing Institute of Technology. All right reserved.
引用
收藏
页码：186 / 191
页数：5
相关论文
共 8 条
  • [1] Chou W., Wang S., Research on obstacle avoidance by virtual force for redundant robot, China Mechanical Engineering, 22, 24, pp. 2899-2902, (2011)
  • [2] Zlajpah L., Nemec B., Kinematic control algorithms for on-line obstacle avoidance for redundant manipulators, Proceedings of Conference on Intelligent Robots and Systems, pp. 1898-1900, (2002)
  • [3] Wu X.J., Tang J., Li Q., Et al., Development of a configuration space motion planner for robot in dynamic environment, Robotics and Computer Integrated Manufacturing, 25, pp. 13-31, (2009)
  • [4] Sanchez-Torrubia M.G., Torres-Blanc C., Lopez-Martinez M.A., Pathfinder: A visualization math teacher for actively learning Dijkstra's algorithm, Electronic Notes in Theoretical Computer Science, 224, 1, pp. 151-158, (2009)
  • [5] Flacco F., de Luca A., Khatib O., Motion control of redundant robots under joint constraints: Saturation in the null space, Proceedings of International Conference on Robotics and Automation, pp. 285-292, (2012)
  • [6] Hasan A.T., Ismail N., Hamouda A.M.S., Et al., Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations, Advances in Engineering Software, 41, pp. 359-367, (2010)
  • [7] Choset H., Lynch K., Hutchinson S., Et al., Principles of Robot Motion-Theory, Algorithms, and Implementation, pp. 109-155, (2005)
  • [8] Zhu Y., Zhang T., Song J., Study on the local minima problem of path planning using potential field method in unknown environments, Acta Automatical Sinica, 36, 8, pp. 1122-1129, (2010)
1