Intelligent Control Strategy for Robotic Arm by Using Adaptive Inertia Weight and Acceleration Coefficients Particle Swarm Optimization
Tzuu‐Hseng S. Li, Ping‐Huan Kuo, Ya-Fang Ho, Guan-Hong Liou
- Year
- 2019
- Citations
- 18
- Access
- Open access
Abstract
This paper proposes an intelligent control strategy for enabling a robotic arm to grasp and place water-filled bottles without spilling any of the water. First, the system architecture of a five-degree-of-freedom robotic arm and its mechanical design are introduced. Second, both the forward and inverse kinematics of the robotic arm are derived. The study conducted an experiment in which the designed and implemented robotic arm could grasp a bottle of water and move it to another place. However, if the acceleration or the orientation of the robotic arm were inappropriate, the water in the bottle may be spilled during the movement. Therefore, the proposed strategy applies an inertial measurement unit for obtaining relevant information. According to the obtained information, the velocity curves of each joint could be optimized by adaptive inertia weight and acceleration coefficients particle swarm optimization. Finally, the experimental results demonstrated the feasibility and effectiveness of the proposed method.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002