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Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation
Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Hong Kong, Peoples R China..
Yale Univ, Dept Mech Engn & Mat Sci, New Haven, CT USA..
Hong Kong Univ Sci & Technol, Dept Mech & Aerosp Engn, Hong Kong, Peoples R China..
KTH, Skolan för elektroteknik och datavetenskap (EECS), Intelligenta system, Robotik, perception och lärande, RPL. KTH, Skolan för elektroteknik och datavetenskap (EECS), Centra, Centrum för autonoma system, CAS.ORCID-id: 0000-0003-2965-2953
Visa övriga samt affilieringar
2019 (Engelska)Ingår i: 2019 International Conference on Robotics and Automation (ICRA) / [ed] Howard, A Althoefer, K Arai, F Arrichiello, F Caputo, B Castellanos, J Hauser, K Isler, V Kim, J Liu, H Oh, P Santos, V Scaramuzza, D Ude, A Voyles, R Yamane, K Okamura, A, Institute of Electrical and Electronics Engineers (IEEE), 2019, s. 2153-2160Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Moving a human body or a large and bulky object may require the strength of whole arm manipulation (WAM). This type of manipulation places the load on the robot's arms and relies on global properties of the interaction to succeed-rather than local contacts such as grasping or non-prehensile pushing. In this paper, we learn to generate motions that enable WAM for holding and transporting of humans in certain rescue or patient care scenarios. We model the task as a reinforcement learning problem in order to provide a robot behavior that can directly respond to external perturbation and human motion. For this, we represent global properties of the robot-human interaction with topology-based coordinates that are computed from arm and torso positions. These coordinates also allow transferring the learned policy to other body shapes and sizes. For training and evaluation, we simulate a dynamic sea rescue scenario and show in quantitative experiments that the policy can solve unseen scenarios with differently-shaped humans, floating humans, or with perception noise. Our qualitative experiments show the subsequent transporting after holding is achieved and we demonstrate that the policy can be directly transferred to a real world setting.

Ort, förlag, år, upplaga, sidor
Institute of Electrical and Electronics Engineers (IEEE), 2019. s. 2153-2160
Serie
IEEE International Conference on Robotics and Automation ICRA, ISSN 1050-4729
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
URN: urn:nbn:se:kth:diva-265483DOI: 10.1109/ICRA.2019.8794160ISI: 000494942301099Scopus ID: 2-s2.0-85068443674ISBN: 978-1-5386-6026-3 (tryckt)ISBN: 978-1-5386-6027-0 (digital)OAI: oai:DiVA.org:kth-265483DiVA, id: diva2:1379604
Konferens
2019 International Conference on Robotics and Automation, ICRA 2019; Palais des Congres de Montreal, Montreal; Canada; 20-24 May 2019
Anmärkning

QC 20191217

Tillgänglig från: 2019-12-17 Skapad: 2019-12-17 Senast uppdaterad: 2020-01-31Bibliografiskt granskad

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Kragic, DanicaStork, Johannes A.

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Kragic, DanicaStork, Johannes A.
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Robotik, perception och lärande, RPLCentrum för autonoma system, CAS
Elektroteknik och elektronik

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