保证追逃的协同非线性制导策略
Cooperative Nonlinear Guidance Strategies for Guaranteed Pursuit-Evasion
AI总结：
本文研究三体追逃问题，为逃跑者-防御者团队提出基于几何的协同非线性制导策略，保证在任意初始交战几何下拦截追击者，且无需获知对方策略，误差变量可在预定有限时间内收敛至零。
摘要：
本文研究了一个涉及三个智能体的追逃问题：一个追击者、一个逃跑者和一个防御者。为逃跑者-防御者团队开发了协同制导律，保证防御者在追击者到达逃跑者附近之前将其拦截。与启发式方法、最优控制、微分博弈公式以及最近提出的受时间约束的制导技术不同，本文提出了一种基于几何的解决方案，以保护逃跑者免受追击者来袭威胁。所提策略计算效率高，且随着智能体数量增加有望具有可扩展性。该策略的另一个显著特征是，逃跑者-防御者团队不需要知道追击者的策略，然而对于任意初始交战几何，都能保证对追击者的拦截。进一步证明，逃跑者-防御者团队（或个体）的相关误差变量在预定有限时间内收敛至零，该时间可在三体交战前精确指定。最后，通过在不同交战场景下的仿真，证明了所提协同追逃策略的有效性。
英文摘要：
This paper investigates a pursuit-evasion problem involving three agents: a pursuer, an evader, and a defender. Cooperative guidance laws are developed for the evader-defender team that guarantee interception of the pursuer by the defender before it reaches the vicinity of the evader. Unlike heuristic methods, optimal control, differential game formulation, and recently proposed time-constrained guidance techniques, a geometry-based solution is proposed to safeguard the evader from the pursuer's incoming threat. The proposed strategy is computationally efficient and expected to be scalable as the number of agents increases. Another notable feature of the proposed strategy is that the evader-defender team does not require knowledge of the pursuer's strategy, yet the pursuer's interception is guaranteed for arbitrary initial engagement geometries. It is further shown that the relevant error variables for the evader-defender team (or individual) converge to zero at a prespecified finite time that can be exactly prescribed prior to the three-body engagement. Finally, the effectiveness of the proposed cooperative pursuit-evasion strategy is demonstrated through simulations across diverse engagement scenarios.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
