Leidner, D, Bartels, G, Bejjani, W et al. (2 more authors) (2019) Cognition-enabled robotic wiping: Representation, planning, execution, and interpretation. Robotics and Autonomous Systems, 114. pp. 199-216. ISSN 0921-8890
Abstract
Advanced cognitive capabilities enable humans to solve even complex tasks by representing and processing internal models of manipulation actions and their effects. Consequently, humans are able to plan the effect of their motions before execution and validate the performance afterwards. In this work, we derive an analog approach for robotic wiping actions which are fundamental for some of the most frequent household chores including vacuuming the floor, sweeping dust, and cleaning windows. We describe wiping actions and their effects based on a qualitative particle distribution model. This representation enables a robot to plan goal-oriented wiping motions for the prototypical wiping actions of absorbing, collecting and skimming. The particle representation is utilized to simulate the task outcome before execution and infer the real performance afterwards based on haptic perception. This way, the robot is able to estimate the task performance and schedule additional motions if necessary. We evaluate our methods in simulated scenarios, as well as in real experiments with the humanoid service robot Rollin’ Justin.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 Elsevier B.V. All rights reserved. This is an author produced version of a paper published in Robotics and Autonomous Systems. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | AI reasoning methods; Action and effect representation; Compliant manipulation; Service robotics |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Apr 2019 13:55 |
Last Modified: | 08 Dec 2019 01:40 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.robot.2018.11.018 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144535 |