论文标题

拉斯:风险意识的群存储

RASS: Risk-Aware Swarm Storage

论文作者

Arseneault, Samuel, Vielfaure, David, Beltrame, Giovanni

论文摘要

在机器人技术中,数据采集通常在未知环境探索中起关键作用。例如,存储有关探索地形或环境中自然危险的地形的信息可以告知机器人的决策过程。因此,至关重要的是安全存储这些数据并将其迅速用于机器人系统的操作员。在像机器人群这样的分散系统中,这需要一些挑战。为了解决这些问题,我们建议RASS是一种分散的风险意识群存储和路由机制,该机制仅依赖于邻居之间的本地信息共享来建立存储和路由健身。我们通过在基于物理的模拟器中进行彻底的实验测试我们的系统,并通过物理实验测试其现实世界的适用性。我们获得令人信服的可靠性,路由速度和群存储容量的结果。

In robotics, data acquisition often plays a key part in unknown environment exploration. For example, storing information about the topography of the explored terrain or the natural dangers in the environment can inform the decision-making process of the robots. Therefore, it is crucial to store these data safely and to make it available quickly to the operators of the robotic system. In a decentralized system like a swarm of robots, this entails several challenges. To address them, we propose RASS, a decentralized risk-aware swarm storage and routing mechanism, which relies exclusively on local information sharing between neighbours to establish storage and routing fitness. We test our system through thorough experiments in a physics-based simulator and test its real-world applicability with physical experiments. We obtain convincing reliability, routing speeds, and swarm storage capacity results.

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