Online 3D Frontier-Based UGV and UAV Exploration Using Direct Point Cloud Visibility

Jason Williams, Shu Jiang, Matthew O'brien, Glenn Wagner, Emili Hernandez, Mark Cox, Alex Pitt, Ron Arkin, Nicolas Hudson

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

5 Scopus citations

Abstract

While robots have long been proposed as a tool to reduce human personnel's exposure to danger in subterranean environments, these environments also present significant challenges to the development of these robots. Fundamental to this challenge is the problem of autonomous exploration. Frontier-based methods have been a powerful and successful approach to exploration, but complex 3D environments remain a challenge when online employment is required. This paper presents a new approach that addresses the complexity of operating in 3D by directly modelling the boundary between observed free and unobserved space (the frontier), rather than utilising dense 3D volumetric representations. By avoiding a representation involving a single map, it also achieves scalability to problems where Simultaneous Localisation and Matching (SLAM) loop closures are essential. The approach enabled a team of seven ground and air robots to autonomously explore the DARPA Subterranean Challenge Urban Circuit, jointly traversing over 8 km in a complex and communication denied environment.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages263-270
Number of pages8
ISBN (Electronic)9781728164229
DOIs
StatePublished - Sep 14 2020
Event2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020 - Karlsruhe, Germany
Duration: Sep 14 2020Sep 16 2020

Publication series

NameIEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems
Volume2020-September

Conference

Conference2020 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2020
Country/TerritoryGermany
CityKarlsruhe
Period09/14/2009/16/20

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