Pair-Navi: Peer-to-Peer Indoor Navigation with Mobile Visual SLAM

Abstract

Existing indoor navigation solutions usually require pre-deployed comprehensive location services with precise indoor maps and, more importantly, all rely on dedicatedly installed or existed infrastructure. In this paper, we present Pair-Navi, an infrastructure-free indoor navigation system that circumvents all these requirements by reusing a previous traveler's (i.e. leader) trace experience to navigate future users (i.e. followers) in a Peer-to-Peer (P2P) mode. Our system leverages the advances of visual SLAM on commercial smartphones. Visual SLAM systems, however, are vulnerable to environmental dynamics in the precision and robustness and involve intensive computation that prohibits real-time applications. To combat environmental changes, we propose to cull non-rigid contexts and keep only the static and rigid contents in use. To enable real-time navigation on mobiles, we decouple and reorganize the highly coupled SLAM modules for leaders and followers. We implement Pair-Navi on commodity smartphones and validate its performance in three diverse buildings. Our results show that Pair-Navi achieves an immediate navigation success rate of 98.6%, which maintains as 83.4% even after two weeks since the leaders' traces were collected, outperforming the state-of-the-art solutions by >50%. Being truly infrastructure-free, Pair-Navi sheds lights on practical indoor navigations for mobile users.