<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-05-31T01:14:08Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/10047" metadataPrefix="oai_dc">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/10047</identifier><datestamp>2026-02-03T12:30:30Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37959</setSpec></header><metadata><oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
   <dc:title>Towards a Shared Control Navigation Function: Efficiency Based Command Modulation</dc:title>
   <dc:creator>Fernández-Carmona, Manuel</dc:creator>
   <dc:creator>Peula-Palacios, José Manuel</dc:creator>
   <dc:creator>Urdiales-García, Amalia Cristina</dc:creator>
   <dc:creator>Sandoval-Hernández, Francisco</dc:creator>
   <dc:subject>Redes neuronales artificiales</dc:subject>
   <dc:subject>Shared control</dc:subject>
   <dc:subject>Navigation function</dc:subject>
   <dc:subject>Potential fields</dc:subject>
   <dc:subject>Mixed initiative control</dc:subject>
   <dc:subject>Power wheelchairs</dc:subject>
   <dc:subject>Assistive robotics</dc:subject>
   <dc:description>This paper presents a novel shared control algorithm for robotized&#xd;
wheelchairs. The proposed algorithm is a new method to extend&#xd;
autonomous navigation techniques into the shared control domain. It reactively&#xd;
combines user’s and robot’s commands into a continuous function&#xd;
that approximates a classic Navigation Function (NF) by weighting input&#xd;
commands with NF constraints. Our approach overcomes the main drawbacks&#xd;
of NFs -calculus complexity and limitations on environment&#xd;
modeling- so it can be used in dynamic unstructured environments. It also&#xd;
benefits from NF properties: convergence to destination, smooth paths&#xd;
and safe navigation. Due to the user’s contribution to control, our function&#xd;
is not strictly a NF, so we call it a pseudo-navigation function (PNF)&#xd;
instead.</dc:description>
   <dc:description>Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.</dc:description>
   <dc:date>2015-07-07T11:16:33Z</dc:date>
   <dc:date>2015-07-07T11:16:33Z</dc:date>
   <dc:date>2015</dc:date>
   <dc:date>2015-07-07</dc:date>
   <dc:type>conference output</dc:type>
   <dc:identifier>http://hdl.handle.net/10630/10047</dc:identifier>
   <dc:identifier>http://orcid.org/0000-0001-9235-7856</dc:identifier>
   <dc:language>eng</dc:language>
   <dc:relation>International work-conference on Artificial Neural Networks</dc:relation>
   <dc:relation>Palma de Mallorca, Islas Baleares, Spain</dc:relation>
   <dc:relation>Junio 2015</dc:relation>
   <dc:rights>by-nc-nd</dc:rights>
   <dc:rights>open access</dc:rights>
   <dc:format>application/pdf</dc:format>
</oai_dc:dc>
</metadata></record></GetRecord></OAI-PMH>