Data-driven Policy Transfer with Imprecise Perception Simulation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F18%3A00322428" target="_blank" >RIV/68407700:21230/18:00322428 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/18:00322428
Result on the web
<a href="http://cmp.felk.cvut.cz/pub/cmp/articles/svoboda/Pecka-Zimermann-Petrlik-Svoboda-IEEE-RAL-2018.pdf" target="_blank" >http://cmp.felk.cvut.cz/pub/cmp/articles/svoboda/Pecka-Zimermann-Petrlik-Svoboda-IEEE-RAL-2018.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/LRA.2018.2857927" target="_blank" >10.1109/LRA.2018.2857927</a>
Alternative languages
Result language
angličtina
Original language name
Data-driven Policy Transfer with Imprecise Perception Simulation
Original language description
This paper presents a complete pipeline for learning continuous motion control policies for a mobile robot when only a non-differentiable physics simulator of robot-terrain interactions is available. The multi-modal state estimation of the robot is also complex and difficult to simulate, so we simultaneously learn a generative model which refines simulator outputs. We propose a coarse-to-fine learning paradigm, where the coarse motion planning is alternated with guided learning and policy transfer to the real robot. The policy is jointly optimized with the generative model. We evaluate the method on a real-world platform.
Czech name
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
<a href="/en/project/GA17-08842S" target="_blank" >GA17-08842S: Robust motion planning and control on rough unstructured terrain</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Robotics and Automation Letters
ISSN
2377-3766
e-ISSN
2377-3766
Volume of the periodical
3
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
6
Pages from-to
3916-3921
UT code for WoS article
000441444700031
EID of the result in the Scopus database
2-s2.0-85063308179