AGVS Path Planning Agorithm in Complex Environments

In the field of warehousing and logistics, automatic guided truck system (AGVS) has the merits of high reliability and flexibility, but with the increase of the complexity of its working environment, the difficulty of path planning also increases. Aiming at the problem of low efficiency and easy conflict in AGVS path planning in complex environment, this paper proposed an improved AGVS path planning algorithm based on hierarchical distributed framework. Firstly, in order to improve the search efficiency of the algorithm in the path planning process, the evaluation function of the traditional A^* algorithm was improved and fused with the bidirectional Floyd algorithm to increase the path smoothness, and the global optimal AGVS path is finally obtained. Secondly, the AGVS kinematics modeling was established, and the key nodes in the global optimal path were taken as temporary target points. By adjusting the initial poses of the robot and optimizing the evaluation function, the AGVS local path planning was completed appying the DWA algorithm to the temporary target points. Finally, AGVS collaborative planning strategy was introduced to achieve unified scheduling of inter-AGVS motion by assigning task priorities to AGVS, reducing the probability of conflicts between mobile machines, improving the robustness of AGVS path planning algorithm. Matlab simulation results show that the proposed improved algorithm can generate collision-free paths in both simple and complex environments. In complex environments, AGVS path length planned by the improved algorithm is shortened by 2.26% compared with that planned by the traditional A^* algorithm. In the process of AGVS motion, the angular velocity and the linear velocity of the mobile robot are always maintained within -0.4~0.4 rad/s, and 0.6~1.2 m/s, which conforms to the kinematic characteristics of the mobile robot.