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Rope through Loop Insertion for Robotic Knotting: A Virtual Magnetic Field Formulation
Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden.
Computer Vision and Active Perception Lab., Centre for Autonomous Systems, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden. (AASS)ORCID-id: 0000-0003-3958-6179
2016 (Engelska)Rapport (Övrigt vetenskapligt)
Abstract [en]

Inserting an end of a rope through a loop is a common and important action that is required for creating most types of knots. To perform this action, we need to pass the end of the rope through an area that is enclosed by another segment of rope. As for all knotting actions, the robot must for this exercise control over a semi-compliant and flexible body whose complex 3d shape is difficult to perceive and follow. Additionally, the target loop often deforms during the insertion. We address this problem by defining a virtual magnetic field through the loop's interior and use the Biot Savart law to guide the robotic manipulator that holds the end of the rope. This approach directly defines, for any manipulator position, a motion vector that results in a path that passes through the loop. The motion vector is directly derived from the position of the loop and changes as soon as it moves or deforms. In simulation, we test the insertion action against dynamic loop deformation of different intensity. We also combine insertion with grasp and release actions, coordinated by a hybrid control system, to tie knots in simulation and with a NAO robot.

Ort, förlag, år, upplaga, sidor
Stockholm, 2016. , s. 8
Nationell ämneskategori
Datavetenskap (datalogi) Datorseende och robotik (autonoma system)
Identifikatorer
URN: urn:nbn:se:oru:diva-71571ISBN: 978-91-7729-218-0 (tryckt)OAI: oai:DiVA.org:oru-71571DiVA, id: diva2:1280220
Tillgänglig från: 2019-01-18 Skapad: 2019-01-18 Senast uppdaterad: 2019-01-23Bibliografiskt granskad

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Stork, Johannes Andreas

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Stork, Johannes Andreas
Datavetenskap (datalogi)Datorseende och robotik (autonoma system)

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