论文标题
部分可观测时空混沌系统的无模型预测
Decentralized Vision-Based Byzantine Agent Detection in Multi-Robot Systems with IOTA Smart Contracts
论文作者
论文摘要
多机器人系统和分布式分类帐技术(DLTS)的交汇处有多个机会。在这项工作中,我们研究了新的DLT解决方案(例如IOTA)的潜力,用于以分散的方式检测多机器人系统中的异常和拜占庭式药物。传统的区块链方法不适用于连通性条件不理想的现实世界网络和分散的机器人系统。为了解决这个问题,我们利用了与IOTA智能合约的耐受性和拜占庭式协作决策过程的最新进展。我们展示了如何将基于视觉异常的工作和变更检测应用于在同一环境中运行的多个机器人中检测拜占庭式药物。我们表明,IOTA智能合约增加了低计算开销,同时允许在多机器人系统中建立信任。提出的方法有效地基于不同机器人提交的图像的比较以及对异常的检测以及它们之间的变化有效地实现了拜占庭机器人的检测。
Multiple opportunities lie at the intersection of multi-robot systems and distributed ledger technologies (DLTs). In this work, we investigate the potential of new DLT solutions such as IOTA, for detecting anomalies and byzantine agents in multi-robot systems in a decentralized manner. Traditional blockchain approaches are not applicable to real-world networked and decentralized robotic systems where connectivity conditions are not ideal. To address this, we leverage recent advances in partition-tolerant and byzantine-tolerant collaborative decision-making processes with IOTA smart contracts. We show how our work in vision-based anomaly and change detection can be applied to detecting byzantine agents within multiple robots operating in the same environment. We show that IOTA smart contracts add a low computational overhead while allowing to build trust within the multi-robot system. The proposed approach effectively enables byzantine robot detection based on the comparison of images submitted by the different robots and detection of anomalies and changes between them.