Online inspection path planning for autonomous 3D modeling using a micro-aerial vehicle

Soohwan Song, Sungho Jo

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

62 Scopus citations

Abstract

In this paper, we propose a novel algorithm for planning exploration paths to generate 3D models of unknown environments by using a micro-aerial vehicle (MAV). Our algorithm initially determines a next-best-view (NBV) that maximizes information gain and plans a collision-free path to reach the NBV. Along the path, the MAV explores the greatest unknown area although it sometimes misses minor unreconstructed region, such as a hole or a sparse surface. To cover such a region, we propose an online inspection algorithm that consistently provides an optimal coverage path toward the NBV in real time. The algorithm iteratively refines an inspection path according to the acquired information until the modeling of a specific local area is complete. We evaluated the proposed algorithm by comparing it with other state-of-the-art approaches through simulated experiments. The results show that our algorithm outperforms the other approaches in both exploration and 3D modeling scenarios.

Original languageEnglish
Title of host publicationICRA 2017 - IEEE International Conference on Robotics and Automation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6217-6224
Number of pages8
ISBN (Electronic)9781509046331
DOIs
StatePublished - 21 Jul 2017
Event2017 IEEE International Conference on Robotics and Automation, ICRA 2017 - Singapore, Singapore
Duration: 29 May 20173 Jun 2017

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2017 IEEE International Conference on Robotics and Automation, ICRA 2017
Country/TerritorySingapore
CitySingapore
Period29/05/173/06/17

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