Parking spot estimation and mapping method for mobile robots

Thomas Westfechtel, Kazunori Ohno, Naoki Mizuno, Ryunosuke Hamada, Shotaro Kojima, Satoshi Tadokoro

研究成果: Article査読

3 被引用数 (Scopus)

抄録

Self-driving vehicles rely on detailed semantic maps of the environment for operating. In this letter, we propose a method to autonomously generate such a semantic map enriched with knowledge of parking spot locations. Our method detects and uses parked vehicles in the surroundings to estimate parking lot topology and infer vacant parking spots via a graph-based approach. We show that our method works for parking lot structures in different environments, such as structured parking lots, unstructured/unmarked parking lots, and typical suburban environments. Using the proposed graph-based approach to infer the parking lot structure, we can extend the estimated parking spots by 57%, averaged over six different areas with ten trials each. We also show that the accuracy of our algorithm increases when combining multiple trials over multiple days. With ten trials combined, we managed to estimate the whole parking lot structure and detected all parking spots in four out of the six evaluated areas.

本文言語English
ページ(範囲)3371-3378
ページ数8
ジャーナルIEEE Robotics and Automation Letters
3
4
DOI
出版ステータスPublished - 2018 10

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 生体医工学
  • 人間とコンピュータの相互作用
  • 機械工学
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用
  • 制御と最適化
  • 人工知能

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