| Compared with the neat and orderly layout of equipment in traditional workshops,the layout of equipment in flexible workshops is flexible and complex due to production needs.Therefore,the flexible workshop environment puts forward higher requirements on the path planning capability of the handling robot.In order to improve the planning efficiency of the path planning algorithm and the operation safety of the handling robot,this paper proposes an improved ant colony algorithm for path planning.Based on the grid map environment,the proposed algorithm is simulated and experimentally verified,and provides a reference for the path planning research of the handling robot in the flexible workshop environment.The specific research work of this paper is as follows:(1)A global path planning method based on Gaussian distribution pheromone volatilization mechanism ant colony optimization algorithm(GD-ACO)is proposed,which effectively improves the planning efficiency of the algorithm and the safety of the handling robot.Since the pheromone of the basic ant colony algorithm maintains a fixed value in the global search,it is difficult to meet the requirements of path search,so an improved ant colony algorithm with volatile pheromone obeying Gaussian distribution is proposed.At the same time,the unqualified paths are filtered through distance constraints to reduce the accumulation of invalid pheromones,and an elite ant strategy is implemented.For the distribution of special obstacles,heuristic function is improved.(2)A local path planning algorithm based on grid transformation and a local cubic uniform B-spline path smoothing algorithm based on increased path selection are proposed,which effectively improve the efficiency of local path planning and the continuity of handling robot movement.For the problem of dynamic obstacles,the global path is first obtained by using the GD-ACO algorithm.Then,in the local obstacle prediction part of the handling robot,the grid transformation strategy of static rasterization of dynamic obstacles is used for secondary path planning.Smooth the path according to the result of global path planning.(3)A path tracking controller based on backstepping control is designed to achieve fast and accurate tracking of the target path by the handling robot.Firstly,the Pioneer3DX robot is selected as the handling robot,and the kinematic model of the handling robot is established,and the path tracking controller is designed based on the backstepping control.Under the premise of avoiding collision with obstacles,this control strategy can enable the handling robot to quickly and accurately move to the target position following the target path to complete the path tracking task.(4)An actual flexible workshop map environment is constructed to carry out path planning experiments for handling robots.The experimental results verify the effectiveness and feasibility of the path planning algorithm proposed in this paper.First,the working environment of the handling robot is abstracted based on the real flexible workshop environment,and the environment modeling is carried out by the grid method.Then,the target path is obtained based on the GD-ACO algorithm and the path smoothing algorithm.Finally,the path tracking experiment is completed based on the backstepping control strategy.In summary,this paper studies the tasks of path planning,path smoothing and path tracking in the flexible workshop environment of the handling robot,and solves the key problems of low efficiency of the basic ant colony optimization algorithm and poor driving safety of the handling robot.Provide effective reference for path planning research in flexible workshop environment. |
