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

Reiya Takemura, Genya Ishigami

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665460262
DOIs
Publication statusPublished - 2022
Event2022 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2022 - Bedford, United Kingdom
Duration: 2022 Sep 202022 Sep 22

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2022-September

Conference

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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Perception-aware Receding Horizon Path Planning for UAVs with LiDAR-based SLAM'. Together they form a unique fingerprint.

Cite this