基于双旋Lyapunov矢量场的无人机避障算法

Obstacle avoidance algorithm for UAV based on bi-rotation Lyapunov vector fields

提出一种基于双旋Lyapunov矢量场的无人机避障算法.首先,建立无人机和障碍物的模型,并根据无人机有限时间是否会侵犯障碍物安全圆设计避障判定规则;然后,基于最小侧向偏移量原则选定避障机动中无人机速度旋转方向为最优避障方向,选定其反方向为矢量场旋转方向,定义成功避障的标准并进行证明;最后,通过建立的障碍物合并规则提升避障效率,使得上述方法适用于未知环境下的无人机在线避障.仿真结果表明,在无人机性能约束下,所提出的算法对动态和静态障碍都能有效避障,算法性能优于Dubins路径和人工势场法.

A bi-rotation Lyapunov vector fields based obstacle avoidance algorithm（BLBOAA） is proposed for unmanned aerial vehicles（UAVs）. Firstly, the models of UAV and obstacle are established, and the decision rules of obstacle are established based on an assessment of whether UAV would rush into the safety circle within a finite time. Then, based on the principle of minimum lateral offset, the optimal obstacle avoidance direction is selected from rotation direction of UAV＇s velocity and its reverse direction is selected as vector field rotation direction. Then, criterion of successful obstacle avoidance is defined and proved. Finally, the established rule of obstacles combination improves the effecienty of obstacle avoidance, and BLBOAA is suitable for on-line obstacle avoidance under the uncertain environment. Simulation results show that the UAV can avoid the dynamic and static obstacles effectively under the dynamic constraint, and the performance of the proposed algorithm is better than that of the Dubins path and artificial potential field.