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Collaborative Programming of Conditional Robot Tasks

Willibald, Christoph and Eiband, Thomas and Lee, Dongheui (2020) Collaborative Programming of Conditional Robot Tasks. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020-10-25 - 2020-10-29, Las Vegas, NV, USA (Virtual). doi: 10.1109/iros45743.2020.9341212. ISBN 978-172816212-6. ISSN 2153-0858.

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Conventional robot programming methods are not suited for non-experts to intuitively teach robots new tasks. For this reason, the potential of collaborative robots for production cannot yet be fully exploited. In this work, we propose an active learning framework, in which the robot and the user collaborate to incrementally program a complex task. Starting with a basic model, the robot's task knowledge can be extended over time if new situations require additional skills. An on-line anomaly detection algorithm therefore automatically identifies new situations during task execution by monitoring the deviation between measured- and commanded sensor values. The robot then triggers a teaching phase, in which the user decides to either refine an existing skill or demonstrate a new skill. The different skills of a task are encoded in separate probabilistic models and structured in a high-level graph, guaranteeing robust execution and successful transition between skills. In the experiments, our approach is compared to two state-of-the-art Programming by Demonstration frameworks on a real system. Increased intuitiveness and task performance of the method can be shown, allowing shop-floor workers to program industrial tasks with our framework.

Item URL in elib:https://elib.dlr.de/139209/
Document Type:Conference or Workshop Item (Speech)
Title:Collaborative Programming of Conditional Robot Tasks
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Willibald, ChristophUNSPECIFIEDhttps://orcid.org/0000-0003-3579-4130UNSPECIFIED
Eiband, ThomasUNSPECIFIEDhttps://orcid.org/0000-0002-1074-9504UNSPECIFIED
Lee, DongheuiUNSPECIFIEDhttps://orcid.org/0000-0003-1897-7664UNSPECIFIED
Journal or Publication Title:2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:Yes
Keywords:Learning from Demonstration; Programming by Demonstration; Human-Robot Collaboration; Intuitive Programming; Interactive Robot Learning
Event Title:2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Event Location:Las Vegas, NV, USA (Virtual)
Event Type:international Conference
Event Start Date:25 October 2020
Event End Date:29 October 2020
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Intuitive Human-Robot Interface [SY]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Willibald, Christoph
Deposited On:07 Dec 2020 11:11
Last Modified:24 Apr 2024 20:40

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