Automatic task scheduling and collision-free path planning for multi-task optimization is a great challenge in various industrial applications. It is a typical coupling problem between task sequence optimization and collision-free path planning. When each task is considered as an area, the problem’s complexity and difficulty will be significantly increased. Task visited sequence, task region entry point optimization, and task switching collision-free path planning should be considered for trade-offs. This paper presents a novel automatic approach to solve task scheduling and collision-free path planning for the multi-areas problem. The proposed method decomposes the problem into two components: task sequence optimization problem and optimal collision-free path planning problem. Firstly, each task is simplified to a point based on the task equivalent center method, and then the task visited sequence is optimized based on Lin Kernighan Heuristic (LKH) algorithm and task equivalent center cost matrix. Secondly, a collision-free optimal tour obtained by performing the rubber-band algorithm (RBA) task entry point optimization and collision-free path planning. Finally, there are three major types of scenarios discussed in this paper: task planning in a complex environment, multi-task planning, and multi-mixed tasks planning in a complex environment, designed to demonstrate the proposed feasibility multi-task planning algorithm. The results show that the presented approach could find a feasible collision-free task visit tour in various complex multi-tasks planning.
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Gao, W., Liu, C., Zhan, Y. et al. Automatic task scheduling optimization and collision-free path planning for multi-areas problem. Intel Serv Robotics 14, 583–596 (2021). https://doi.org/10.1007/s11370-021-00381-8
- Task scheduling
- Path planning