dc.creator | Pérez Hurtado de Mendoza, Ignacio | es |
dc.creator | Pérez Jiménez, Mario de Jesús | es |
dc.creator | Zhang, Gexiang | es |
dc.creator | Orellana Martín, David | es |
dc.date.accessioned | 2021-03-17T11:08:44Z | |
dc.date.available | 2021-03-17T11:08:44Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Pérez Hurtado de Mendoza, I., Pérez Jiménez, M.d.J., Zhang, G. y Orellana Martín, D. (2018). Robot Path Planning using Rapidly-Exploring Random Trees: A Membrane Computing Approach. En ICCCC 2018: 7th International Conference on Computers Communications and Control Oradea, Romania: IEEE Computer Society. | |
dc.identifier.isbn | 978-1-5386-1934-6 | es |
dc.identifier.uri | https://hdl.handle.net/11441/106207 | |
dc.description.abstract | Methods based on Rapidly-exploring Random Trees
(RRTs) have been in use in robotics to solve motion planning
problems for nearly two decades. On the other hand, in the
membrane computing framework, models based on Enzymatic
Numerical P systems (ENPS) have been applied to robot controllers.
These controllers handle the power of motors according
to motion commands usually generated by planning algorithms,
but today there is a lack of planning algorithms based on
membrane computing for robotics. With this motivation, we
provide a new variant of ENPS called Random Enzymatic Numerical
P systems with Proteins and Shared Memory (RENPSM)
addressed to implement RRT algorithms and we illustrate it by
presenting a model for path planning of mobile robots based on
the bidirectional RRT algorithm. A software for RENPSM has
been developed within the Robot Operating System (ROS) and
simulation experiments have been conducted by means of the
Pioneer 3-DX robot simulation platform. | es |
dc.description.sponsorship | Ministerio de Economía, Industria y Competitividad TIN2017-89842-P | es |
dc.description.sponsorship | National Natural Science Foundation of China 61672437 | es |
dc.description.sponsorship | National Natural Science Foundation of China No. 61702428 | es |
dc.description.sponsorship | Sichuan Science and Technology Program 18ZDYF2877 | es |
dc.description.sponsorship | Sichuan Science and Technology Program 18ZDYF1985 | es |
dc.format | application/pdf | es |
dc.format.extent | 10 | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | ICCCC 2018: 7th International Conference on Computers Communications and Control (2018). | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Robot Path Planning using Rapidly-Exploring Random Trees: A Membrane Computing Approach | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | TIN2017-89842-P | es |
dc.relation.projectID | 61672437 | es |
dc.relation.projectID | 61702428 | es |
dc.relation.projectID | 18ZDYF2877 | es |
dc.relation.projectID | 18ZDYF1985 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/8390434 | es |
dc.identifier.doi | 10.1109/ICCCC.2018.8390434 | es |
dc.contributor.group | Universidad de Sevilla. TIC193: Computación Natural | es |
dc.eventtitle | ICCCC 2018: 7th International Conference on Computers Communications and Control | es |
dc.eventinstitution | Oradea, Romania | es |
dc.relation.publicationplace | New York, USA | es |
dc.contributor.funder | Ministerio de Economia, Industria y Competitividad (MINECO). España | es |
dc.contributor.funder | National Natural Science Foundation of China | es |
dc.contributor.funder | Sichuan Science and Technology Program | es |