桥式起重机三维吊装路径规划

Three Dimensional Hoisting Path Planning for Overhead Crane

桥式起重机吊装路径规划研究大部分是在二维环境下进行的,在三维环境中的路径规划研究较少,且目前关于桥式起重机的三维路径规划方法多是基于传感器导航的Srinivas算法。该算法的参数是根据经验得到的,且在不同环境中很难准确选择最优值。所建立的环境模型障碍物约为两个,无法证明在更多障碍物的环境中是否仍然可以保证路径最优且安全防撞。鉴于智能算法的优势以及在机器人领域中的成功应用,提出了基于改进蚁群算法的三维吊装路径规划方案。建立静态且环境已知的桥式起重机三维作业环境模型,利用栅格法划分空间,将桥式起重机所吊重物最大摆动距离与其安全通过障碍物的距离之和设为安全距离,且对蚁群算法的启发函数、适应度函数、信息素更新公式等进行了改进,使其应用于桥式起重机三维环境的吊装路径规划。Matlab仿真研究结果证明了该方案的可行性与有效性。

Mostly, the research on overhead crane hoisting path planning is carried out in the 2D environment, less research in three -dimensional environment is found;and at present,most of the 3D path planning methods are the Srinivas algorithm based on navigation In this algorithm, the parameters are determined according to the experience, and it is difficult to select the optimal values under different enviromnents. Moreover, the obstacles of environmental model are only about two or so, and it cannot be proved that in the environment with more obstacles, it is still possible to ensure the optimal path and safe collision avoidance. In view of the advantages of the intelligent algorithm and the successful application in the field of robots, the 3D hoisting path planning scheme based on improved ant colony algorithm is proposed. The 3D static working environment model of the overhead crane is established, using the grid method to divide the space, the sum of the maximum swing distance of overhead crane with hoisted weight and the distance of safety going through the obstacle is used as a safe distance ;and the heuristic function of the ant colony algorithm, the fitness function, and the pheromone update fornmla are improved for adopting in hoisting path planning in 3D environment of the overhead crane. Matlab simulation results verify the feasibility and effectiveness of the propsed scheme.