A comparison of humanoid robot simulators: a quantitative approach Ayala, Angel, Cruz Naranjo, Francisco, Campos, Diego, Rubio, Rodrigo, Fernandes, Bruno and Dazeley, Richard 2020, A comparison of humanoid robot simulators: a quantitative approach, in ICDL-EpiRob 2020 : Proceedings of the 10th IEEE International Conference on Development and Learning and Epigenetic Robotics, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 1-6, doi: 10.1109/ICDL-EpiRob48136.2020.9278116. Attached Files Name Description MIMEType Size Downloads Title A comparison of humanoid robot simulators: a quantitative approach Author(s) Ayala, Angel Cruz Naranjo, Francisco orcid.org/0000-0002-1131-3382 Campos, Diego Rubio, Rodrigo Fernandes, Bruno Dazeley, Richard orcid.org/0000-0002-6199-9685 Conference name IEEE Computational Intelligence Society. International Conference (10th : 2020 : Online from Valparaiso, Chile) Conference location Online from Valparaiso, Chile Conference dates 2020/10/26 - 2020/10/30 Title of proceedings ICDL-EpiRob 2020 : Proceedings of the 10th IEEE International Conference on Development and Learning and Epigenetic Robotics Editor(s) [Unknown] Publication date 2020 Series IEEE Computational Intelligence Society International Conference Start page 1 End page 6 Total pages 6 Publisher Institute of Electrical and Electronics Engineers Place of publication Piscataway, N.J. Keyword(s) robotic simulator simulation tools comparison humanoid robot NAO Summary Research on humanoid robotic systems involves a considerable amount of computational resources, not only for the involved design but also for its development and subsequent implementation. For robotic systems to be implemented in realworld scenarios, in several situations, it is preferred to develop and test them under controlled environments in order to reduce the risk of errors and unexpected behavior. In this regard, a more accessible and efficient alternative is to implement the environment using robotic simulation tools. This paper presents a quantitative comparison of Gazebo, Webots, and V-REP, three simulators widely used by the research community to develop robotic systems. To compare the performance of these three simulators, elements such as CPU, memory footprint, and disk access are used to measure and compare them to each other. In order to measure the use of resources, each simulator executes 20 times a robotic scenario composed by a NAO robot that must navigate to a goal position avoiding a specific obstacle. In general terms, our results show that Webots is the simulator with the lowest use of resources, followed by V-REP, which has advantages over Gazebo, mainly because of the CPU use. Notes This conference was originally scheduled to be held in Valparaiso, Chile, however due to the 2020 COVID Pandemic, the event was held online. ISBN 9781728173061 Language eng DOI 10.1109/ICDL-EpiRob48136.2020.9278116 Indigenous content off HERDC Research category E1 Full written paper - refereed Persistent URL http://hdl.handle.net/10536/DRO/DU:30147910 Document type: Conference Paper Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Mon, 08 Feb 2021, 07:20:13 EST Mon, 08 Feb 2021, 10:39:17 EST Tue, 09 Feb 2021, 04:01:12 EST Tue, 09 Feb 2021, 05:04:38 EST Wed, 24 Feb 2021, 11:18:40 EST Wed, 24 Feb 2021, 11:20:44 EST Wed, 24 Feb 2021, 15:01:40 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 1 times in Scopus Search Google Scholar Access Statistics: 15 Abstract Views, 4 File Downloads  -  Detailed Statistics Created: Mon, 08 Feb 2021, 10:39:17 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.