论文标题
约束驱动的最佳控制，以避免出现的蜂群和捕食者
Constraint-Driven Optimal Control for Emergent Swarming and Predator Avoidance
论文作者
论文摘要
在这封信中，我们提出了一个约束驱动的最佳控制框架，该框架在约束的2D环境中实现了新兴的集群群。我们制定了一个分散的最佳控制问题，其中包括安全，羊群和捕食者避免限制。我们明确地得出了约束兼容性的条件，并提出了一个事件驱动的约束松弛方案，我们将其映射到等效的有限状态机，该机器直觉地描述了系统中每个代理的行为。与其最大程度地减少控制努力，因为它在生态启发的机器人技术文献中很常见，而是在我们的方法中最小化了每个代理与它们最有效的运动速度的偏差。最后，我们证明了我们在有和不存在捕食者的情况下模拟方法。
In this letter, we present a constraint-driven optimal control framework that achieves emergent cluster flocking within a constrained 2D environment. We formulate a decentralized optimal control problem that includes safety, flocking, and predator avoidance constraints. We explicitly derive conditions for constraint compatibility and propose an event-driven constraint relaxation scheme, which we map to an equivalent finite state machine that intuitively describes the behavior of each agent in the system. Instead of minimizing control effort, as it is common in the ecologically-inspired robotics literature, in our approach, we minimize each agent's deviation from their most efficient locomotion speed. Finally, we demonstrate our approach in simulation both with and without the presence of a predator.
