arXiv Machine Learning By Feng Liu (Beijing Jiaotong University), Kejia Li (Beijing Jiaotong University), Zhiwei Yang (DiDi Company), Chunwei Yang (DiDi Company), Qun Li (DiDi Company), Guobin Wu (DiDi Company), Qiang Ni (Lancaster University), Ruipeng Gao (Beijing Jiaotong University)

Tracking Large-scale Shared Bikes with Inertial Motion Learning in GNSS Blocked Environments

Read the original on arXiv Machine Learning →

arXiv:2605. 07412v2 Announce Type: replace Abstract: 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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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