Research Article
Research on an Algorithm of Six Degrees of Freedom Manipulator Arm Moving with End Trajectory
@INPROCEEDINGS{10.1007/978-3-030-67874-6_36, author={Yun-sheng Chen}, title={Research on an Algorithm of Six Degrees of Freedom Manipulator Arm Moving with End Trajectory}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Six degrees of freedom Manipulator arm End trajectory motion Particle swarm}, doi={10.1007/978-3-030-67874-6_36} }- Yun-sheng Chen
Year: 2021
Research on an Algorithm of Six Degrees of Freedom Manipulator Arm Moving with End Trajectory
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_36
Abstract
Under manipulator trajectory motion algorithm, the time consumption of manipulator motion is long, and the stability coefficient is low, and the accuracy of obstacle avoidance is poor. An algorithm that six degree of freedom manipulator moves with end trajectory based on particle swarm optimization was proposed. By analyzing the positive solution of kinematics and inverse solution of kinematics of manipulator, the expected pose of manipulator was obtained to realize the analysis of manipulator trajectory. According to the constraint condition of the short time consumption of motion, the high accuracy of obstacle avoidance and the strong motion stability, the model that six degree of freedom manipulator ARM moved with end trajectory is built. The model was subdivided into particle swarm optimization algorithm to realize the solution of model. Then, some parameters such as initial position and speed of particle swarm were set, and particle swarm fitness function was calculated to get the optimal solution. Finally, we determined whether the current optimal solution was the global optimal solution. Thus, we obtained the optimal planning results that the manipulator moves with the end trajectory. Experiment shows that the time consumption of manipulator motion is short. The average accuracy of obstacle avoidance is 95%. The stability coefficient is high. This algorithm can effectively solve the problem of current algorithm, which has practicality.
