DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Probabilistic Effect Prediction through Semantic Augmentation and Physical Simulation

Bauer, Adrian Simon and Schmaus, Peter and Stulp, Freek and Leidner, Daniel (2020) Probabilistic Effect Prediction through Semantic Augmentation and Physical Simulation. In: 2019 International Conference on Robotics and Automation, ICRA 2019, pp. 9278-9284. IEEE. IEEE International Conference on Robotics and Automation (ICRA), 31. May - 31. Aug 2020, Paris, France. doi: 10.1109/ICRA40945.2020.9197477. ISBN 978-153866026-3. ISSN 10504729.

[img] PDF

Official URL: https://ieeexplore.ieee.org/document/9197477


Nowadays, robots are mechanically able to perform highly demanding tasks, where AI-based planning methods are used to schedule a sequence of actions that result in the desired effect. However, it is not always possible to know the exact outcome of an action in advance, as failure situations may occur at any time. To enhance failure tolerance, we propose to predict the effects of robot actions by augmenting collected experience with semantic knowledge and leveraging realistic physics simulations. That is, we consider semantic similarity of actions in order to predict outcome probabilities for previously unknown tasks. Furthermore, physical simulation is used to gather simulated experience that makes the approach robust even in extreme cases. We show how this concept is used to predict action success probabilities and how this information can be exploited throughout future planning trials. The concept is evaluated in a series of real world experiments conducted with the humanoid robot Rollin’ Justin.

Item URL in elib:https://elib.dlr.de/134290/
Document Type:Conference or Workshop Item (Speech)
Title:Probabilistic Effect Prediction through Semantic Augmentation and Physical Simulation
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Bauer, Adrian Simonadrian.bauer (at) dlr.dehttps://orcid.org/0000-0002-1171-4709
Schmaus, PeterPeter.Schmaus (at) dlr.dehttps://orcid.org/0000-0002-6639-0967
Stulp, FreekFreek.Stulp (at) dlr.dehttps://orcid.org/0000-0001-9555-9517
Leidner, Danieldaniel.leidner (at) dlr.dehttps://orcid.org/0000-0001-5091-7122
Date:June 2020
Journal or Publication Title:2019 International Conference on Robotics and Automation, ICRA 2019
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.1109/ICRA40945.2020.9197477
Page Range:pp. 9278-9284
Keywords:Robotics, Task and Motion Planning, Humanoid, Reasoning, Probabilistic Reasoning, Physical Simulation, Semantics
Event Title:IEEE International Conference on Robotics and Automation (ICRA)
Event Location:Paris, France
Event Type:international Conference
Event Dates:31. May - 31. Aug 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 - Vorhaben Intelligente Mobilität (old), R - On-Orbit Servicing [SY]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Cognitive Robotics
Institute of Robotics and Mechatronics (since 2013) > Autonomy and Teleoperation
Deposited By: Bauer, Adrian
Deposited On:03 Dec 2020 13:37
Last Modified:11 Mar 2022 16:07

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.