Authors

Abstract

The existing obstacle avoidance control algorithms for wheeled agricultural warehouse handling robots are prone to the local optimal solution in the process of path optimization and collision can occur easily occur during multi-robot simultaneous operation. Given this, the obstacle avoidance of wheeled agricultural warehouse handling robots was explored in this study, and an obstacle avoidance path planning algorithm for wheeled agricultural handling robots in warehouse based on improved ACO-DWA algorithm was proposed. Then, the moving trajectory of agricultural warehouse handling robots during handling process was studied, and their spatial kinematics equation was given. Next, the real-time pose of agricultural warehouse handling robots was detected, and their motion path was planned considering the real-time position of obstacles and the target locations of handling. In addition, the obstacle avoidance controlling quantity of agricultural warehouse handling robots was calculated according to the deviation between the pose of robots and the planned path. Supported by a controller, the obstacle avoidance control work of agricultural warehouse handling robots was realized. It was concluded through the effect experiment that compared with the traditional method, the improved ACO-DWA algorithm designed in this study significantly reduced the number of collisions between agricultural robots, and through practical application, the proposed algorithm can meet the needs of improving warehouse logistics management efficiency.

Abstract in Chinese

针对现有轮式农业机器人仓储搬运避障控制算法存在的路径寻优易陷入局部最优解，及多机器人同时作业易发生碰撞等问题，对轮式农业机器人的仓库避障控制进行了研究，并提出提出了一种基于改进ACO-DWA算法的轮式农业机器人仓库搬运避障路径规划算法；对农业机器人仓储机器人搬运过程中的移动轨迹进行了研究，给出了机器人空间运动学方程。检测农业农业机器人仓储搬运实时位姿，考虑障碍物实时位置和搬运目标地点，规划机器人移动路径。根据农业机器人位姿与规划路径之间的偏差，计算农业机器人仓储搬运避障控制量，在控制器的支持下，实现农业机器人仓储搬运避障控制工作。通过效果测试实验得出结论：与传统方法相比，本文所设计的改进ACO-DWA算法，农业机器人之间发生碰撞的次数也显著少于传统避障控制算法，经实际应用能够满足提升仓储物流管理效率的需求。