About: Deepbots: A Webots-Based Deep Reinforcement Learning Framework for Robotics

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Deepbots: A Webots-Based Deep Reinforcement Learning Framework for Robotics Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Deepbots: A Webots-Based Deep Reinforcement Learning Framework for Robotics
Creator	Kirtas, M Passalis, N Tefas, A Tsampazis, K
Source	PMC
abstract	Deep Reinforcement Learning (DRL) is increasingly used to train robots to perform complex and delicate tasks, while the development of realistic simulators contributes to the acceleration of research on DRL for robotics. However, it is still not straightforward to employ such simulators in the typical DRL pipeline, since their steep learning curve and the enormous amount of development required to interface with DRL methods significantly restrict their use by researchers. To overcome these limitations, in this work we present an open-source framework that combines an established interface used by DRL researchers, the OpenAI Gym interface, with the state-of-the-art Webots robot simulator in order to provide a standardized way to employ DRL in various robotics scenarios. Deepbots aims to enable researchers to easily develop DRL methods in Webots by handling all the low-level details and reducing the required development effort. The effectiveness of the proposed framework is demonstrated through code examples, as well as using three use cases of varying difficulty.
has issue date	2020-05-06(xsd:dateTime)
bibo:doi	10.1007/978-3-030-49186-4_6
has license	no-cc
sha1sum (hex)	449a049426c86405a52f73efbe56427171c567c3
schema:url	https://doi.org/10.1007/978-3-030-49186-4_6
resource representing a document's title	Deepbots: A Webots-Based Deep Reinforcement Learning Framework for Robotics
has PubMed Central identifier	PMC7256566
schema:publication	Artificial Intelligence Applications and Innovations
resource representing a document's body	covid:449a049426c86405a52f73efbe56427171c567c3#body_text
is schema:about of	named entity 'simulator' named entity 'demonstrated' named entity 'USED BY' named entity 'ACCELERATION' named entity 'PERFORM' named entity 'LIMITATIONS' named entity 'SOURCE' named entity 'code' named entity 'provide' named entity 'steep' named entity 'Gym' named entity 'robots' named entity 'limitations' named entity 'robot simulator' named entity 'Webots' named entity 'Deep Reinforcement Learning' named entity 'Webots' named entity 'probability' named entity 'inverted pendulum' named entity 'robot' named entity 'learning curve' named entity 'robot' named entity 'DRL' named entity 'ROS' named entity 'Webots' named entity 'DRL' named entity 'ROS' named entity 'Gazebo' named entity 'sensor' named entity 'Webots' named entity 'OpenAI Gym' named entity 'DRL' named entity 'robotics' named entity 'design patterns' named entity 'robotic arms' named entity '1.2' named entity 'actuators' named entity 'DDPG' named entity 'unsupervised learning' named entity 'closed source' named entity 'Policy Gradient' named entity 'DRL' named entity 'E-puck' named entity 'DRL' named entity 'robot' named entity 'iCub' named entity 'Webots' named entity 'Python-based' named entity 'Deep Learning' named entity 'DRL' named entity 'DRL' named entity 'robot' named entity 'actuators' named entity 'robot' named entity 'research purposes' named entity 'DRL' named entity 'software development' named entity 'robot' named entity 'mobile robot' named entity 'OpenAI Gym' named entity 'ROS' named entity 'Webots' named entity 'step function' named entity 'algorithm' named entity 'robot simulator' named entity 'sensor' named entity 'PyTorch' named entity '1.1' named entity 'Webots' named entity 'robot' named entity 'DRL' named entity 'robot' named entity 'velocity' named entity 'Webots' named entity 'DRL' named entity 'logic' named entity 'Webots' named entity 'robotics' named entity 'Java' named entity 'robot'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software