Research On Trajectory Planning Control of Industrial Manipulator Based on ALO Algorithm - Liang, Xianxia; Yue, Longfei; Li, Yupeng; Cheng, Longxue; Sun, Litao (International Journal of Industrial Engineering: Theory, Applications and Practice, 2025)
Aiming at the shortcomings of the ant lion optimization algorithm (ALO) in industrial manipulator trajectory planning, such as long path length, time-consuming rotation time, and uneven path, an improved ALO (IALO) is proposed. Firstly, the population is initialized by cubic chaotic mapping to improve the quality of ant lion population. Secondly, the trust region mutation is used to improve the location update mode of ant lion population and balance the global search ability and local mining ability. Finally, the Gaussian mutation disturbance strategy is used to improve the location update mode of ant lion population and enhance the ability of the algorithm to jump out of local optimization. Taking trajectory length, rotation time, and redundancy rate as indicators, compared with the ABC algorithm and classic ALO, this algorithm has a shorter path length and less rotation time.