Incrementally-deployable Indoor Navigation with Automatic Trace Generation

ieee international conference computer and communications(2019)

引用 26|浏览82
暂无评分
摘要
Despite years of research attention, localization-based indoor navigation has not found wide-spread practical use, largely due to the high burden on deployment and bootstrapping. Lightweight peer-to-peer navigation systems that use a leader-follower model have recently been proposed to alleviate these burdens. However, typical peer-to-peer navigation suffers from poor scalability and flexibility as navigation is only possible over pre-collected leader paths. In this paper, we present FollowUs, an easily-deployable (bootstrap-free) and scalable indoor navigation system. In addition to robust navigation through real-time trace-following, FollowUs integrates cloud services to process and combine traces at large scale. Optionally, it can also leverage floor plans to further enhance navigation efficiency. We design and implement FollowUs, including mobile app and cloud services. Experimental results from a company-internal beta release show that 91% of FollowUs’ spatial errors on reaching destinations to be 3m or less, and 95% of navigation instructions are shown to users within a 4-step error margin during navigation.
更多
查看译文
关键词
Hafnium
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要