An improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators
In this article, we present an improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators. Specifically, we not only focused on the position for the manipulator end-effectors but also considered their posture in the course of trajectory planni...
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| Published in | International journal of advanced robotic systems Vol. 15; no. 5; p. 172988141879956 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
London, England
SAGE Publications
01.09.2018
Sage Publications Ltd SAGE Publishing |
| Subjects | |
| Online Access | Get full text |
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| Abstract | In this article, we present an improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators. Specifically, we not only focused on the position for the manipulator end-effectors but also considered their posture in the course of trajectory planning and obstacle avoidance. We introduced boundaries for Cartesian space components to optimize the attractive field function. Moreover, the manipulator achieved a reasonable speed to move to the target pose, regardless of the difference between the initial pose and target pose. We proved the stability using Lyapunov stability theory by introducing velocity feedforward, when the manipulator moved along a continuous trajectory. Considering the shape of the manipulator joints and obstacles, we set up the collision detection model by projecting the obstacles to link coordinates. In this case, establishing the repulsive field between the nearest points on every joint and obstacles with the closest distance was sufficient for achieving obstacle avoidance for redundant manipulators. The simulation results based on a nine-degree-of-freedom hyper-redundant manipulator, which was designed and made in our laboratory, fully substantiated the efficacy and superiority of the proposed method. |
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| AbstractList | In this article, we present an improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators. Specifically, we not only focused on the position for the manipulator end-effectors but also considered their posture in the course of trajectory planning and obstacle avoidance. We introduced boundaries for Cartesian space components to optimize the attractive field function. Moreover, the manipulator achieved a reasonable speed to move to the target pose, regardless of the difference between the initial pose and target pose. We proved the stability using Lyapunov stability theory by introducing velocity feedforward, when the manipulator moved along a continuous trajectory. Considering the shape of the manipulator joints and obstacles, we set up the collision detection model by projecting the obstacles to link coordinates. In this case, establishing the repulsive field between the nearest points on every joint and obstacles with the closest distance was sufficient for achieving obstacle avoidance for redundant manipulators. The simulation results based on a nine-degree-of-freedom hyper-redundant manipulator, which was designed and made in our laboratory, fully substantiated the efficacy and superiority of the proposed method. |
| Author | He, Shuai Xu, Zhenbang Wang, Wenrui Zhu, Mingchao Wang, Xiaoming He, Junpei |
| Author_xml | – sequence: 1 givenname: Wenrui orcidid: 0000-0002-3023-9659 surname: Wang fullname: Wang, Wenrui – sequence: 2 givenname: Mingchao surname: Zhu fullname: Zhu, Mingchao email: mingchaozhu@gmail.com – sequence: 3 givenname: Xiaoming surname: Wang fullname: Wang, Xiaoming – sequence: 4 givenname: Shuai surname: He fullname: He, Shuai – sequence: 5 givenname: Junpei surname: He fullname: He, Junpei – sequence: 6 givenname: Zhenbang surname: Xu fullname: Xu, Zhenbang |
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| Keywords | attractive potential field obstacle avoidance Trajectory planning velocity feedforward repulsive potential field |
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| SubjectTerms | Collision dynamics Computer simulation Obstacle avoidance Potential fields Redundancy Stability Trajectory planning |
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