Newest papers

Safe Multi-Robot Collaboration With Uniform Exclusion Using Trust

Thomas Kaminsky, Áron Vèkássy, Hammad Izhar, Angelia Nedić, Stephanie Gil · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28251 · cited by 0 works (OpenAlex) · open-access PDF

Chinese

我们提供一个算法,作为机器人通信周围的包装器――当机器人试图通过一些接入链接的数据更新其状态时,我们的包装器提供了一组可信的链接,其中一些数据可以安全地集成,以允许任意恶意数据的传输。它通过测试一个有效的信任值――从每个机器人异常探测器收集的数据――使用安全随时有效的推断器来选择这些链接――当机器人试图更新其状态时,我们的包装器提供了一组可信的链接,其中两个数据可以被安全地嵌入:它通过测试一个有效的信任值――数据,但仍然很快学会信任合法的链接。我们只要求检测器在通用任务上更好,但没有使用之前的8个狗,以便在模拟和不限于MG的

Machine translation (Meta M2M100); the English original follows.

Abstract

Robot swarms coordinate through directed, time-varying local communication links, some of which may be compromised to allow the transmission of arbitrary malicious data. We provide an algorithm that acts as a wrapper around robot communication---when a robot seeks to update its state using data from some incoming links, our wrapper provides a subset of trusted links whose data can be safely incorporated. It selects these links by testing a stream of trust values---data collected from an anomaly detector on each robot---using Safe Anytime-Valid Inference. We require only that the detector be better than chance. This wrapper ensures safe and performant autonomy by providing two powerful statistical guarantees: it uniformly excludes all compromised links for all time with high user-chosen probability, but nevertheless quickly learns to trust legitimate links. Both guarantees are vital to secure generic tasks, but no previous work provides them simultaneously without restrictive assumptions on connectivity structure or the number of compromised links that are not guaranteed in practice. We study our Safe Wrapper's performance in hardware for two contrasting tasks---neural implicit mapping and heading consensus---deploying on 3 LoCoBots and 8 GoPiGos, respectively. We provide simulations using trust values sampled from hardware to validate that our approach scales well to swarms of hundreds of robots.

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Topics: Computer science, Anomaly detection, Robot, State (computer science), Computer security, Heading (navigation)

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