Edge-Cloud Based Vehicle SLAM for Autonomous Indoor Map Updating

Zepeng Zhu, Jiajia Liu, Jiadai Wang, Nei Kato

研究成果: Conference contribution

抄録

Map information is of crucial importance to ensure the safety and reliability of vehicle, no matter indoor or outdoor, it should reflect the real-time changes of environment. Existing indoor map update mechanisms have several common limitations such as small update range, long cycle, large amount of update data, high cost and poor currency. Therefore, we present a multi-vehicle collaborative indoor map update scheme based on edge-cloud architecture to realize real-time autonomous map updating. This scheme can be achieved through continuous monitoring, tagging, identification, and layering of the environment during driving process. Compared with traditional map update schemes, experimental results show that our scheme can effectively realize the collaborative map update in indoor environment, enhance the map update efficiency, reduce the update delay, and improve the adaptability of vehicles.

本文言語English
ホスト出版物のタイトル2020 IEEE 92nd Vehicular Technology Conference, VTC 2020-Fall - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728194844
DOI
出版ステータスPublished - 2020 11
イベント92nd IEEE Vehicular Technology Conference, VTC 2020-Fall - Virtual, Victoria, Canada
継続期間: 2020 11 18 → …

出版物シリーズ

名前IEEE Vehicular Technology Conference
2020-November
ISSN(印刷版)1550-2252

Conference

Conference92nd IEEE Vehicular Technology Conference, VTC 2020-Fall
国/地域Canada
CityVirtual, Victoria
Period20/11/18 → …

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 電子工学および電気工学
  • 応用数学

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