EMap: Real-Time Terrain Estimation

Jacobus C. Lock, Fanta Camara, Charles Fox*

*Corresponding author for this work

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

Abstract

Terrain mapping has a many use cases in both land surveyance and autonomous vehicles. Popular methods generate occupancy maps over 3D space, which are sub-optimal in outdoor scenarios with large, clear spaces where gaps in LiDAR readings are common. A terrain can instead be modelled as a height map over 2D space which can iteratively be updated with incoming LiDAR data, which simplifies computation and allows missing points to be estimated based on the current terrain estimate. The latter point is of particular interest, since it can reduce the data collection effort required (and its associated costs) and current options are not suitable to real-time operation. In this work, we introduce a new method that is capable of performing such terrain mapping and inferencing tasks in real-time. We evaluate it with a set of mapping scenarios and show it is capable of generating maps with higher accuracy than an OctoMap-based method.

Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems - 23rd Annual Conference, TAROS 2022, Proceedings
EditorsSalvador Pacheco-Gutierrez, Alice Cryer, Ipek Caliskanelli, Harun Tugal, Robert Skilton
PublisherSpringer Science and Business Media Deutschland GmbH
Pages114-127
Number of pages14
ISBN (Print)9783031159077
DOIs
Publication statusPublished - 1 Sept 2022
Event23rd Annual Conference Towards Autonomous Robotic Systems, TAROS 2022 - Culham, United Kingdom
Duration: 7 Sept 20229 Sept 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13546 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd Annual Conference Towards Autonomous Robotic Systems, TAROS 2022
Country/TerritoryUnited Kingdom
CityCulham
Period7/09/229/09/22

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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