While multiple studies have proposed methods for the formation control of unmanned aerial vehicles (UAV), the trajectories generated are generally unsuitable for tracking targets where the optimum coverage of the target by the formation is required at all times. We propose a path planning approach called the Flux Guided (FG) method, which generates collision-free trajectories while maximising the coverage of one or more targets. We show that by reformulating an existing least-squares flux minimisation problem as a constrained optimisation problem, the paths obtained are $1.5 \times$ shorter and track directly toward the target. Also, we demonstrate that the scale of the formation can be controlled during flight, and that this feature can be used to track multiple scattered targets. The method is highly scalable since the planning algorithm is only required for a sub-set of UAVs on the open boundary of the formation's surface. Finally, through simulating a 3d dynamic particle system that tracks the desired trajectories using a PID controller, we show that the resulting trajectories after time-optimal parameterisation are suitable for robotic controls.
翻译:虽然提出了多种无人驾驶飞行器形成控制方法,但所产生的轨迹通常不适于跟踪需要随时以天体形成最佳覆盖目标的目标。我们提议了一种称为通航向(FG)方法的路径规划方法,这种方法产生无碰撞轨迹,同时最大限度地扩大一个或一个以上目标的覆盖范围。我们表明,通过将现有最小方位流动最小度最小度问题重新定位为限制优化问题,所获得的路径为1.5美元,并直接跟踪目标。此外,我们还表明,在飞行期间可以控制形成该目标的大小,而且这一特性可用于跟踪多个分散的目标。这一方法非常可扩展,因为只需要在天体表面的开放边界上对UAV子集进行规划算法。最后,通过利用PID控制器对跟踪理想轨迹的3D动态粒子系统进行模拟,我们显示,在时间-观察参数化后产生的轨迹轨迹可用于机器人控制。