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Proxemic group behaviors using reciprocal multi-agent navigation

机译:互惠多智能体导航的近邻群体行为

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We present a decentralized algorithm for group-based coherent and reciprocal multi-agent navigation. In addition to generating collision-free trajectories for each agent, our approach is able to simulate macroscopic group movements and proxemic behaviors that result in coherent navigation. Our approach is general, makes no assumptions about the size or shape of the group, and can generate smooth trajectories for the agents. Furthermore, it can dynamically adapt to obstacles or the behavior of other agents. The additional overhead of generating proxemic group behaviors is relatively small and our approach can simulate hundreds of agents in real-time. We highlight its benefits on different benchmarks.
机译:我们提出了一种用于基于组的相干和互惠多智能体导航的分散算法。除了为每个代理生成无碰撞的轨迹外,我们的方法还能够模拟宏观的群体运动和近距离行为,从而导致连贯的导航。我们的方法是通用的,不假设组的大小或形状,并且可以为代理生成平滑的轨迹。此外,它可以动态适应障碍或其他代理的行为。生成近邻组行为的额外开销相对较小,并且我们的方法可以实时模拟数百个代理。我们将重点介绍其在不同基准上的优势。

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