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3D Guidance Law for Maximal Coverage and Target Enclosing with Inherent Safety

2024-04-25 03:38:07
Praveen Kumar Ranjan, Abhinav Sinha, Yongcan Cao
     

Abstract

In this paper, we address the problem of enclosing an arbitrarily moving target in three dimensions by a single pursuer, which is an unmanned aerial vehicle (UAV), for maximum coverage while also ensuring the pursuer's safety by preventing collisions with the target. The proposed guidance strategy steers the pursuer to a safe region of space surrounding the target, allowing it to maintain a certain distance from the latter while offering greater flexibility in positioning and converging to any orbit within this safe zone. Our approach is distinguished by the use of nonholonomic constraints to model vehicles with accelerations serving as control inputs and coupled engagement kinematics to craft the pursuer's guidance law meticulously. Furthermore, we leverage the concept of the Lyapunov Barrier Function as a powerful tool to constrain the distance between the pursuer and the target within asymmetric bounds, thereby ensuring the pursuer's safety within the predefined region. To validate the efficacy and robustness of our algorithm, we conduct experimental tests by implementing a high-fidelity quadrotor model within Software-in-the-loop (SITL) simulations, encompassing various challenging target maneuver scenarios. The results obtained showcase the resilience of the proposed guidance law, effectively handling arbitrarily maneuvering targets, vehicle/autopilot dynamics, and external disturbances. Our method consistently delivers stable global enclosing behaviors, even in response to aggressive target maneuvers, and requires only relative information for successful execution.

Abstract (translated)

在本文中,我们研究了在三维空间中用一个追击器(UAV)围住一个任意运动的靶子的问题,同时确保追击者的安全,防止与目标发生碰撞。所提出的引导策略将追击器引导到位于靶子周围的 safe 区域,同时提供更大的灵活性来确定性和收敛到 safe 区域内的任何轨道。我们的方法的特点在于使用非齐次约束来建模作为控制输入的加速度的车辆,以及采用耦合运动学来精心塑造追击者的引导律。此外,我们还利用Lyapunov Barrier Function的概念作为强大的工具来限制追击器与目标之间的距离,从而确保在定义区域内追击者的安全。为了验证我们算法的有效性和鲁棒性,我们在软件循环(SITL)仿真中实现了高保真度的四旋翼模型,涵盖了各种具有挑战性的目标操纵场景。得到的结果表明,所提出的引导律具有弹性,有效地处理了任意运动目标的车辆/自动驾驶器动力学以及外部干扰。我们的方法始终如一地提供稳定的全局围栏行为,即使在激进的目标操纵响应下也能有效处理,并且只需要相对信息来成功执行。

URL

https://arxiv.org/abs/2404.16312

PDF

https://arxiv.org/pdf/2404.16312.pdf


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