This article proposes a multi-objective function that includes AGV running time, production workshop energy consumption, and machine running efficiency, in response to the problems of path conflicts, single planning objectives, and isolation of planning stages in the current flexible production workshop AGV car planning. Then, the flying mouse algorithm is used to solve the problem using multiple functions. In order to avoid falling into local optima during the solving process, a simulated annealing strategy is incorporated into the flying mouse algorithm. Finally, taking the production of new energy vehicle on-board batteries as an example, a collaborative planning analysis was conducted using the method proposed in this paper. The results showed that the algorithm proposed in this paper can save 30% of running time and improve machine operating efficiency by 22.7%.