Perception-aware Receding Horizon Path Planning for UAVs with LiDAR-based SLAM

Reiya Takemura, Genya Ishigami

研究成果: Conference contribution

抄録

This paper presents a perception-aware path planning framework for unmanned aerial vehicles (UAVs) that explicitly considers perception quality of a light detection and ranging (LiDAR) sensor. The perception quality is quantified based on how scattered feature points are in LiDAR-based simultaneous localization and mapping, which can improve the accuracy of pose estimation of UAVs. In the planning step of a UAV, the proposed framework selects the best path based on the perception quality from a library of candidate paths generated by the rapidly-exploring random trees algorithm. Consequently, the UAV can autonomously fly to a destination in a receding horizon manner. Several simulation trials of the photorealistic environments confirm that our proposed path planner reduces pose estimation error by approximately 85 % on average as compared with a purely-reactive path planner.

本文言語English
ホスト出版物のタイトル2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665460262
DOI
出版ステータスPublished - 2022
イベント2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022 - Bedford, United Kingdom
継続期間: 2022 9月 202022 9月 22

出版物シリーズ

名前IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
2022-September

Conference

Conference2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
国/地域United Kingdom
CityBedford
Period22/9/2022/9/22

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ サイエンスの応用

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