Quantitative evaluation of coarse-to-fine loading strategies for material rehandling

Martin Magnusson, Tomasz Kucner, Achim J. Lilienthal

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

Abstract

Autonomous handling of piled materials is an emerging topic in automation science and engineering. A central question for material rehandling tasks (transporting materials that have been assembled in piles) is 'where to dig, in order to optimise performance'? In particular, we are interested in the application of autonomous wheel loaders to handle piles of gravel. Still, the methodology proposed in this paper relates to granular materials in other applications too. Although initial work on suggesting strategies for where to dig has been done by a few other groups, there has been a lack of structured evaluation of the usefulness of the proposed strategies. In an attempt to further the field, we present a quantitative evaluation of loading strategies; both coarse ones, aiming to maintain a good pile shape over long-term operation; and refined ones, aiming to detect the locally best attack pose for acquiring a good fill grade in the bucket. Using real-world data from a semi-automated test platform, we present an assessment of how previously proposed pile shape measures can be mapped to the amount of material in the bucket after loading. We also present experimental data for long-term strategies, using simulations based on real-world 3D scan data from a production site.

Original languageEnglish
Title of host publication2015 IEEE Conference on Automation Science and Engineering
Subtitle of host publicationAutomation for a Sustainable Future, CASE 2015
PublisherIEEE Computer Society
Pages450-455
Number of pages6
ISBN (Electronic)9781467381833
DOIs
StatePublished - 7 Oct 2015
Externally publishedYes
Event11th IEEE International Conference on Automation Science and Engineering, CASE 2015 - Gothenburg, Sweden
Duration: 24 Aug 201528 Aug 2015

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2015-October
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference11th IEEE International Conference on Automation Science and Engineering, CASE 2015
Country/TerritorySweden
CityGothenburg
Period24/08/1528/08/15

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