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Dual-Arm In-Hand Manipulation Using Visual Feedback
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0002-9171-8768
Yale University.ORCID iD: 0000-0003-4132-1217
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-2078-8854
KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Robotics, Perception and Learning, RPL.ORCID iD: 0000-0003-2965-2953
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we address the problem of executing in-hand manipulation based on visual input. Given an initial grasp, the robot has to change its grasp configuration without releasing the object. We propose a method for in-hand manipulation planning and execution based on information on the object’s shape using a dual-arm robot. From the available information on the object, which can be a complete point cloud but also partial data, our method plans a sequence of rotations and translations to reconfigure the object’s pose. This sequence is executed using non-prehensile pushes defined as relative motions between the two robot arms.

Place, publisher, year, edition, pages
2019. p. 411-418
National Category
Robotics
Identifiers
URN: urn:nbn:se:kth:diva-262881OAI: oai:DiVA.org:kth-262881DiVA, id: diva2:1363053
Conference
IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids) October 15-17, 2019 Toronto, Canada
Note

QC 20191129

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-11-29Bibliographically approved

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Hang, KaiyuSmith, ChristianKragic, Danica

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