无人驾驶拖拉机实时避障路径规划算法

为了实现无人驾驶拖拉机在直线作业时的实时避障路径规划功能，提出一种在改进最短切线法的基础上用五次多项式函数规划路径的避障路径规划算法。针对最短切线法规划的路径曲率不连续、难跟踪控制的问题，首先采用改进最短切线法求相关坐标点，然后基于求得的坐标点用五次多项式函数求解路径，最后得到由两段五次多项式函数曲线和直线组成的曲率连续的避障路径。对避障路径规划算法进行仿真，结果表明，该算法生成路径长度短、实时性好、安全性高。基于常州东风无人驾驶拖拉机的运动学模型设计一种模型预测控制器，在Simulink与CarSim联合仿真平台上对无人驾驶拖拉机的避障路径规划及跟踪控制进行联合仿真，结果表明：与改进最短切线法相比，基于五次多项式函数的路径规划算法规划的路径跟踪控制精度更高，更易于跟踪控制。

Real-time obstacle avoidance path planning algorithm for unmanned tractors

In order to realize the real-time obstacle avoidance path planning function of unmanned tractors in straight-line operation, this study proposed an obstacle avoidance path planning algorithm that used a fifth degree polynomial function to plan the path based on the improved shortest tangent method. To solve the problems of discontinuous curvature and difficult tracking control of the path planned by the shortest tangent method, firstly, the improved shortest tangent method was used to find the relevant coordinate points. Based on the obtained coordinate points, the fifth degree polynomial function was then used to solve the path. Finally, an obstacle avoidance path with continuous curvature composed of polynomial function curves and straight lines was obtained. The obstacle avoidance path planning algorithm was simulated. The simulation results show that the path generated by the proposed algorithm has features of short distance, good real-time performance and high security. A model predictive controller was designed based on the kinematics model of the Changzhou Dongfeng unmanned tractor, and the obstacle avoidance path planning and tracking control of the unmanned tractor were jointly simulated on the Simulink and CarSim co-simulation platform. The simulation results show that, compared with the improved shortest tangent method, the path planning algorithm based on the fifth degree polynomial function has higher precision and easier tracking control.