Existing studies on formation control for unmanned aerial vehicles (UAV) have not considered encircling targets where an optimum coverage of the target is required at all times. Such coverage plays a critical role in many real-world applications such as tracking hostile UAVs. This paper proposes a new path planning approach called the Flux Guided (FG) method, which generates collision-free trajectories for multiple UAVs while maximising the coverage of target(s). Our method enables UAVs to track directly toward a target whilst maintaining maximum coverage. Furthermore, multiple scattered targets can be tracked by scaling the formation during flight. FG is highly scalable since it only requires communication between sub-set of UAVs on the open boundary of the formation's surface. Experimental results further validate that FG generates UAV trajectories $1.5 \times$ shorter than previous work and that trajectory planning for 9 leader/follower UAVs to surround a target in two different scenarios only requires 0.52 seconds and 0.88 seconds, respectively. The resulting trajectories are suitable for robotic controls after time-optimal parameterisation; we demonstrate this using a 3d dynamic particle system that tracks the desired trajectories using a PID controller.
翻译:关于无人驾驶航空器(无人驾驶航空器)的编造控制的现有研究没有考虑到在任何时候都需要最佳目标覆盖的环绕目标。这种覆盖在许多现实应用中发挥着关键作用,例如跟踪敌对无人驾驶航空器。本文件提出一个新的路径规划方法,称为“FlUL 向导(FG)法”,为多个无人驾驶航空器生成无碰撞轨迹,同时最大限度地扩大目标的覆盖范围。我们的方法使无人驾驶航空器能够直接跟踪目标,同时保持最大覆盖范围。此外,通过在飞行期间扩大编造,可以跟踪多个分散的目标。FG非常可伸缩,因为它只需要在编造地表开放边界上的无人驾驶飞行器子集之间进行通信。实验结果进一步证实,FG生成UAV 轨迹比以往工作短1.5美元\time,9个领导/追随者UAV在两种不同情况下围绕目标的轨迹规划只需要0.52秒和0.88秒。由此产生的轨迹在时间-视点PID参数化后适合机器人控制。我们用3个动态粒子系统展示了这一轨道。