The point to point trajectory planning based on the ant lion optimiser
Jinchao Guo, Desheng Yan, Hong Song Cao, Zhengke Jiang · International Journal of Automation and Control · 2016
This paper proposes a new method to optimise trajectory for the robot arm. Quadrinomial and quintic polynomials are utilised in joint space to describe point to point trajectory. The ant lion optimiser (ALO) is introduced to ensure searching the global optimal. Dynamic weight is adopted to improve the search ability of the new algorithm. Considering a maximum pre-defined joint torque of the robot manipulator and the ability to avoid obstacles in the work space, the objective function is given for ALO to minimising motion space and time. The simulation is accomplished for different situation with or without obstacle in the workspace to verify the validity of the new algorithm. The different simulation results generated by ALO, GA and QPSO are given to inspect ALOs accuracy. The results show ALO has extremely strong ability to find the global optimal and even less time consumed compared with GA and QPSO.