AI RESEARCH
Tracking Large-scale Shared Bikes with Inertial Motion Learning in GNSS Blocked Environments
arXiv CS.AI
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ArXi:2605.07412v1 Announce Type: cross Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environments where only inertial navigation systems work, such as urban canyons. Despite decades of research, localization using only low-cost inertial sensors still faces challenges such as cumulative drifts and poor robustness caused by filtering methods. Furthermore, sensors such as visual and LiDAR could provide reliable measurements, but they are not suitable for large-scale deployment.