Multi-objective Path Planning of Single Delivery Robot in Epidemic Control Campus
Nianbo Kang, Hongguo Wang, Quan-Ke Pan · 2022 41st Chinese Control Conference (CCC) · 2022
In order to improve the delivery efficiency of single delivery robot in the campus environment of epidemic closure and control, in this paper, an MMOEA/D algorithm that combines the multi-objective evolutionary algorithm MOEA/D based on decomposition strategy and local search strategy is proposed. Firstly, the campus environment model is established, and the A* algorithm is used to plan the path matrix between the target points. Then, with the shortest path length and the shortest average delay time as the goal, the MMOEA/D algorithm is used to determine the traversal sequence of each target point to get the best path. In this paper, MMOEA/D algorithm is compared with MOEA/D algorithm and NSGA-II algorithm. The experimental results show that the target value and path optimized by the MMOEA/D algorithm is better.