Combining Ant Colony Algorithm And Quadric Bezier Curve Unmanned Vehicle Route Planning

The path planning technology of unmanned vehicle is an important part of the research field of unmanned vehicle.It is the premise of unmanned vehicle completing complex tasks.According to the needs of the research topic,in order to plan the path that meets the kinematics constraints of unmanned vehicle and avoids obstacles safely in the obstacle environment,a path planning method based on ant colony algorithm and quartic Bezier curve fusion is proposed.Based on the analysis of several improved algorithm ideas,the classical ant colony algorithm is improved by improving the heuristic function,initial pheromone allocation,transition probability and global pheromone update.A local path planning method for quadratic Bezier curve is proposed.Firstly,the starting position and the target position are determined.Then,the five control points needed for the quartic Bezier curve are determined by minimizing the difference between the maximum curvature and the minimum curvature of the curve.Then,the quartic Bezier curve is determined according to the five control points.Finally,the optimal route is selected from several alternative curves.Aiming at the fusion optimization of UAV path planning,an ant colony algorithm combined with quadratic Bezier curve is proposed.Under the raster map,the improved classical ant colony algorithm is used to plan the global shortest path from the starting point to the target point.Then,the path is divided into a finite number of locations,and the constraints of starting position,target position and location are generated between each two locations.Quartic Bezier curves with continuous curvature constraints and safe obstacle avoidance are formed.Finally,a continuous driving route of unmanned vehicle is formed.The simulation experiment is carried out by using MATLAB software.The simulation results show that the method is effective and feasible.