abstract

Coupled inverse-forward models for action execution leading to tool-use in a humanoid robot

Authors:

Guido Schillaci,

Verena Vanessa Hafner,

Bruno LaraAuthors Info & Claims

HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction

Pages 231 - 232

https://doi.org/10.1145/2157689.2157770

Published: 05 March 2012 Publication History

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Abstract

We propose a computational model based on inverse-forward model pairs for the simulation and execution of actions. The models are implemented on a humanoid robot and are used to control reaching actions with the arms. In the experimental setup a tool has been attached to the left arm of the robot extending its covered action space. The preliminary investigations carried out aim at studying how the use of tools modifies the body scheme of the robot. The system performs action simulations before the actual executions. For each of the arms, predicted end-effector positions are compared with the desired one and the internal pair presenting the lowest error is selected for action execution. This allows the robot to decide on performing an action either with its hand alone or with the one with the attached tool.

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Cited By

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Yordanova MHafner V(2024)Memory-Feedback Controllers for Lifelong Sensorimotor Learning in Humanoid RobotsFrom Animals to Animats 1710.1007/978-3-031-71533-4_21(275-286)Online publication date: 7-Sep-2024
https://doi.org/10.1007/978-3-031-71533-4_21
Schubotz REbel SElsner BWeiss PWörgötter F(2023)Tool mastering today – an interdisciplinary perspectiveFrontiers in Psychology10.3389/fpsyg.2023.119179214Online publication date: 16-Jun-2023
https://doi.org/10.3389/fpsyg.2023.1191792
Bechtle SDas NMeier F(2023)Multimodal Learning of Keypoint Predictive Models for Visual Object ManipulationIEEE Transactions on Robotics10.1109/TRO.2022.320450939:2(1212-1224)Online publication date: Apr-2023
https://doi.org/10.1109/TRO.2022.3204509
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Index Terms

Coupled inverse-forward models for action execution leading to tool-use in a humanoid robot
1. Computing methodologies
  1. Machine learning

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Information

Published In

HRI '12: Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction

March 2012

518 pages

ISBN:9781450310635

DOI:10.1145/2157689

General Chairs:
Holly Yanco
University of Massachusetts Lowell, USA
,
Aaron Steinfeld
Carnegie Mellon University, USA
,
Program Chairs:
Vanessa Evers
University of Amsterdam, The Netherlands
,
Odest Chadwicke Jenkins
Brown University, USA

In-Cooperation

IEEE-RAS: Robotics and Automation

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 March 2012

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HRI'12

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HRI'12: International Conference on Human-Robot Interaction

March 5 - 8, 2012

Massachusetts, Boston, USA

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Overall Acceptance Rate 268 of 1,124 submissions, 24%

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Cited By

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Yordanova MHafner V(2024)Memory-Feedback Controllers for Lifelong Sensorimotor Learning in Humanoid RobotsFrom Animals to Animats 1710.1007/978-3-031-71533-4_21(275-286)Online publication date: 7-Sep-2024
https://doi.org/10.1007/978-3-031-71533-4_21
Schubotz REbel SElsner BWeiss PWörgötter F(2023)Tool mastering today – an interdisciplinary perspectiveFrontiers in Psychology10.3389/fpsyg.2023.119179214Online publication date: 16-Jun-2023
https://doi.org/10.3389/fpsyg.2023.1191792
Bechtle SDas NMeier F(2023)Multimodal Learning of Keypoint Predictive Models for Visual Object ManipulationIEEE Transactions on Robotics10.1109/TRO.2022.320450939:2(1212-1224)Online publication date: Apr-2023
https://doi.org/10.1109/TRO.2022.3204509
Mellmann HTaliaronak VHafner V(2023)Towards an Anticipatory Mechanism for Complex Decisions in a Bio-Hybrid BeehiveConcurrency, Specification and Programming10.1007/978-3-031-26651-5_7(145-173)Online publication date: 5-May-2023
https://doi.org/10.1007/978-3-031-26651-5_7
Bechtle SHammoud BRai AMeier FRighetti L(2021)Leveraging Forward Model Prediction Error for Learning Control2021 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA48506.2021.9561396(4445-4451)Online publication date: 30-May-2021
https://doi.org/10.1109/ICRA48506.2021.9561396
Duminy NNguyen SDuhaut D(2019)Learning a Set of Interrelated Tasks by Using a Succession of Motor Policies for a Socially Guided Intrinsically Motivated LearnerFrontiers in Neurorobotics10.3389/fnbot.2018.0008712Online publication date: 8-Jan-2019
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Winfield AHafner V(2019)Anticipation in RoboticsHandbook of Anticipation10.1007/978-3-319-91554-8_73(1587-1615)Online publication date: 2-Aug-2019
https://doi.org/10.1007/978-3-319-91554-8_73
Lara BAstorga DMendoza-Bock EPardo MEscobar ECiria A(2018)Embodied Cognitive Robotics and the learning of sensorimotor schemesAdaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems10.1177/105971231878067926:5(225-238)Online publication date: 1-Oct-2018
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Zhang THu FDeng YNie MLiu TWu XLuo D(2018)Self-developing Proprioception-Based Robot Internal ModelsIntelligence Science II10.1007/978-3-030-01313-4_34(321-332)Online publication date: 2-Oct-2018
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Winfield AHafner V(2017)Anticipation in RoboticsHandbook of Anticipation10.1007/978-3-319-31737-3_73-1(1-30)Online publication date: 23-Sep-2017
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