Robotic Arm Path Planning Based on Three-Dimensional Artificial Potential Field
Hsien-I Lin, Ming-Feng Hsieh
- 发表年份
- 2018
- 引用次数
- 9
摘要
This paper focuses on the problem of collision avoidance by an three-dimensional artificial potential field (APF) for a robotic arm. In this paper, a force sensor is adopted to estimate obstacle positions on a reference trajectory to a target. This helps a robotic arm move in a safe path in an unknown 3D environment. Compared to traditional APF methods, the major contribution of our proposed algorithm is the implementation of rotational repulsive force fields that provide a robotic arm a feasible direction to avoid obstacles in a 3D space. The experimental results validated that the robotic arm could avoid unknown obstacles on the reference trajectory until the target was reached. Also, the robotic arm learned to improve the trajectory according to the previous trials in a short-term run.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991