arXivDaily arXiv每日学术速递 周一至周五更新
​通知:联邦节假日调休:哥伦布日 / 原住民日(Columbus Day / Indigenous Peoples' Day),今日(13日)无更新。
arXiv 2302.10292cs.ROcs.AI

AERoS:自主机器人群体中涌现行为的保证

AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms

University of Bristol(布里斯托大学);University of York(约克大学)

Dhaminda B. Abeywickrama, James Wilson, Suet Lee, Greg Chance, Peter D. Winter, Arianna Manzini, Ibrahim Habli, Shane Windsor, Sabine Hauert, Kerstin Eder

AI总结:

本文提出AERoS流程,遵循AMLAS指南,用于保证自主机器人群体中涌现行为的安全性,并通过公共衣帽间机器人案例进行验证。

摘要:

群体行为并非被显式设计,而是个体智能体之间及其与环境交互的涌现结果。这种涌现功能对安全保证构成了挑战。本文的主要贡献是提出一个名为AERoS的流程,用于自主机器人群体中涌现行为的安全保证,该流程遵循《自主系统中机器学习保证指南》(AMLAS)。我们通过一个以运营公共衣帽间的机器人群体为中心的案例研究来探索我们提出的流程。

英文摘要:

The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety assurance. The main contribution of this paper is a process for the safety assurance of emergent behaviour in autonomous robotic swarms called AERoS, following the guidance on the Assurance of Machine Learning for use in Autonomous Systems (AMLAS). We explore our proposed process using a case study centred on a robot swarm operating a public cloakroom.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑