CALU: collision avoidance with localization uncertainty (demonstration)

Daniel Claes,Daniel Hennes,Wim Meeussen,Karl Tuyls

AAMAS（2012）

引用 3|浏览25

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摘要

CALU is a multi-robot collision avoidance system based on the velocity obstacle paradigm. In contrast to previous approaches, we alleviate the strong requirement for perfect sensing (i.e. global positioning) using Adaptive Monte-Carlo Localization on a per-agent level.

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关键词

localization uncertainty,velocity obstacle paradigm,per-agent level,multi-robot collision avoidance system,global positioning,strong requirement,Adaptive Monte-Carlo Localization,previous approach

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