摘要
机器人是智能仓储系统的重要设备,路径规划是物流机器人实现自主导航的关键技术之一。首先通过栅格法对智能仓储系统环境进行建模。其次,采用A^(*)算法求解从起始位置到目标位置的初始路径。最后,针对A^(*)算法规划路径中存在较多转折的问题,提出了一种基于L型路径趋势的改进A;算法。遍历初始路径中的转折节点,在没有障碍物的情况下,用与之构成回路的对角节点替换当前转弯节点,从而实现路径平滑。仿真实验表明,就算法运行时间而言,曼哈顿距离更适用于智能仓储物流机器人的路径规划;基于L型路径趋势的改进A^(*)算法,以微小的算法运行时间代价,有效减少了局部路径中的转折次数和累计转弯角度,提高了智能仓储物流机器人的作业安全和效率。
Robot is an important equipment in intelligent warehouse system. Path planning is one of the key technologies to realize autonomous navigation of Logistics robot. Firstly, the intelligent warehouse system environment is modeled by grid method. Secondly, A^(*)algorithm is used to solve the initial path from the starting position to the target position. Finally,an improved A^(*)algorithm based on L-shaped path trend is proposed to solve the problem that there are many turns in A^(*)algorithm’s path planning. For path smoothing, traversing the turn node in the initial path, in the absence of obstacles, the current turning node is replaced with the diagonal node that forms the loop with it. The simulation results show that Manhattan distance is more suitable for path planning of intelligent warehouse logistics robot in terms of algorithm running time;the improved A;algorithm based on the L-shaped path trend can effectively reduce the turning\cumulative turning angle in the local path at a small cost of algorithm running time and improve the operation safety and efficiency of the Logistics robot.
作者
林俊
LIN Jun(Longyan University,School of Physics and Mechatronics Engineering,Longyan364000,China)
出处
《三明学院学报》
2021年第6期51-58,共8页
Journal of Sanming University
基金
福建省中青年教师教育科研项目(JAT190753)。
