Multi-Robot Adversarial Resilience using Control Barrier Functions

Matthew Cavorsi, Beatrice Capelli, Lorenzo Sabattini, Stephanie Gil
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引用次数: 6

Abstract

—In this paper we present a control barrier function- based (CBF) resilience controller that provides resilience in a multi-robot network to adversaries. Previous approaches provide resilience by virtue of specific linear combinations of multiple control constraints. These combinations can be difficult to find and are sensitive to the addition of new constraints. Unlike previous approaches, the proposed CBF provides network resilience and is easily amenable to multiple other control constraints, such as collision and obstacle avoidance. The inclusion of such con- straints is essential in order to implement a resilience controller on realistic robot platforms. We demonstrate the viability of the CBF-based resilience controller on real robotic systems through case studies on a multi-robot flocking problem in cluttered environments with the presence of adversarial robots.
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基于控制障碍函数的多机器人对抗弹性
在本文中,我们提出了一种基于控制屏障函数(CBF)的弹性控制器,该控制器在多机器人网络中为对手提供弹性。以前的方法通过多个控制约束的特定线性组合来提供弹性。这些组合可能很难找到,并且对添加的新约束很敏感。与以前的方法不同,所提出的CBF提供了网络弹性,并且很容易适应多种其他控制约束,例如碰撞和避障。为了在现实机器人平台上实现弹性控制器,包含这些约束是必不可少的。通过对存在敌对机器人的混乱环境中的多机器人群集问题的案例研究,我们证明了基于cbf的弹性控制器在真实机器人系统上的可行性。
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