论文标题
通过地方控制规则和在线全球目标选择策略放大随机自主代理
Herding stochastic autonomous agents via local control rules and online global target selection strategies
论文作者
论文摘要
在本文中，我们提出了一组简单而有效的局部控制规则，以使一组“牧民代理”收集并包含在所需的区域中，这是飞机上的非合作随机性“目标”集合。我们研究了提出的策略对目标代理数量变化的鲁棒性以及在牧民附近时所感受到的反击力量的强度。广泛的数值模拟证实了该方法的有效性，并通过ROS对市售机器人剂的更现实验证进行了补充。
In this Paper we propose a simple yet effective set of local control rules to make a group of "herder agents" collect and contain in a desired region an ensemble of non-cooperative stochastic "target agents" in the plane. We investigate the robustness of the proposed strategies to variations of the number of target agents and the strength of the repulsive force they feel when in proximity of the herders. Extensive numerical simulations confirm the effectiveness of the approach and are complemented by a more realistic validation on commercially available robotic agents via ROS.
