基于改进RRT算法的无人机航路规划与跟踪方法研究

为了使航路规划算法在三维动态环境下能够快速规划出较优可行航路,基于快速扩展随机树算法(RRT),对规划航路点进行了无人机飞行动力学约束,并且设计了局部航路动态优化策略。针对传统的航路跟踪控制律跟踪较为曲折的航线时跟踪误差较大的问题,通过将规划算法得出的姿态指令引入姿态控制回路的方式,提高了航路跟踪控制算法的快速性与准确性。在此基础上,搭建了无人机验证平台,利用该验证平台完成了无人机自主避障飞行试验,对算法的有效性进行了验证,并对算法性能进行了评估。

Research on a Path Planning and Trajectory Tracking Method for UAVs Based on Improved RRT Algorithm

In order to figure out good and flyable trajectories quickly for UAVs in 3D dynamic environment, a path planning and tracking method for UAV based on the rapidly-exploring random tree (RRT) is proposed in this paper, carries out the UAV flight dynamic constraint on the planned route points, and designs a local route dynamic optimization strategy. Aiming at the problem of large tracking error when the traditional route tracking control law tracks relatively zigzag route, the speed and accuracy of the route tracking control algorithm are improved by introducing the attitude instruction from the planning algorithm into the attitude control loop. On this basis, a UAV verification platform is built in this paper, which is used to complete the autonomous obstacle avoidance flight test of UAV, verify the effectiveness of the algorithm, and evaluate the performance of the algorithm.