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Support relation analysis and decision making for safe robotic manipulation tasks
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0002-2392-7146
Örebro University, School of Science and Technology. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)
Örebro University, School of Science and Technology. (AASS MRO Lab)ORCID iD: 0000-0003-0217-9326
2015 (English)In: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 71, no SI, 99-117 p.Article in journal (Refereed) Published
Abstract [en]

In this article, we describe an approach to address the issue of automatically building and using high-level symbolic representations that capture physical interactions between objects in static configurations. Our work targets robotic manipulation systems where objects need to be safely removed from piles that come in random configurations. We assume that a 3D visual perception module exists so that objects in the piles can be completely or partially detected. Depending on the outcome of the perception, we divide the issue into two sub-issues: 1) all objects in the configuration are detected; 2) only a subset of objects are correctly detected. For the first case, we use notions from geometry and static equilibrium in classical mechanics to automatically analyze and extract act and support relations between pairs of objects. For the second case, we use machine learning techniques to estimate the probability of objects supporting each other. Having the support relations extracted, a decision making process is used to identify which object to remove from the configuration so that an expected minimum cost is optimized. The proposed methods have been extensively tested and validated on data sets generated in simulation and from real world configurations for the scenario of unloading goods from shipping containers.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2015. Vol. 71, no SI, 99-117 p.
Keyword [en]
Scene analysis, Machine learning, Decision making, World models, Robotic manipulation
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-40703DOI: 10.1016/j.robot.2014.12.014ISI: 000357146000010OAI: oai:DiVA.org:oru-40703DiVA: diva2:778509
Projects
Cognitive Robot for Automation of Logistic Processes (RobLog)
Available from: 2015-01-10 Created: 2015-01-10 Last updated: 2017-12-05Bibliographically approved

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Mojtahedzadeh, RasoulBouguerra, AbdelbakiSchaffernicht, ErikLilienthal, Achim J

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