TDLE: 2-D LiDAR Exploration with Hierarchical Planning Using Regional Division

Xuyang Zhao*, Chengpu Yu, Erpei Xu, Yixuan Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Exploration systems are critical for enhancing the autonomy of robots. Due to the unpredictability of the future planning space, existing methods either adopt an inefficient greedy strategy, or require a lot of resources to obtain a global solution. In this work, we address the challenge of obtaining global exploration routes with minimal computing resources. A hierarchical planning framework dynamically divides the planning space into subregions and arranges their orders to provide global guidance for exploration. Indicators that are compatible with the subregion order are used to choose specific exploration targets, thereby considering estimates of spatial structure and extending the planning space to unknown regions. Extensive simulations and field tests demonstrate the efficacy of our method in comparison to existing 2D LiDAR-based approaches. Our code has been made public for further investigation11Available at https://github.com/SeanZsya/tdle.

Original languageEnglish
Title of host publication2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
PublisherIEEE Computer Society
ISBN (Electronic)9798350320695
DOIs
Publication statusPublished - 2023
Event19th IEEE International Conference on Automation Science and Engineering, CASE 2023 - Auckland, New Zealand
Duration: 26 Aug 202330 Aug 2023

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2023-August
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference19th IEEE International Conference on Automation Science and Engineering, CASE 2023
Country/TerritoryNew Zealand
CityAuckland
Period26/08/2330/08/23

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