Probabilistic sensor data processing for robot localization on load-sensing floors
Identifieur interne : 000023 ( Main/Exploration ); précédent : 000022; suivant : 000024Probabilistic sensor data processing for robot localization on load-sensing floors
Auteurs : Maxime Rio [Suisse] ; Francis Colas [France] ; Mihai Andries [France] ; François Charpillet [France]Source :
Abstract
Load-sensing floors are capable of tracking objects without suffering from occlusions nor posing the same privacy issues as cameras. They have been mostly used to analyze human gait as a way of continuous diagnosis but could also be placed alongside robots to help monitoring in specialized institutions, such as elderly care facilities. However, large-scale deployments necessitate cheap sensors which do not necessarily offer the same precision. With more noisy sensors, lighter robots might be difficult to track and precisely localize. In this article, we investigate various models in order to estimate the position of a robot. We experiment with several robots of different weights and compare the models' estimates against ground truth measurements provided by a motion capture system. We show that with standard-sized tiles of 60 cm, we can track even the lighter robots with less than 4 cm of error.
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CS 25233 - 54052 Nancy cedex</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-lorraine.fr/</ref></desc></org></tutelle><tutelle name="UMR7503" active="#struct-441569" type="indirect"><org type="institution" xml:id="struct-441569" status="VALID"><idno type="ISNI">0000000122597504</idno><idno type="IdRef">02636817X</idno><orgName>Centre National de la Recherche Scientifique</orgName><orgName type="acronym">CNRS</orgName><date type="start">1939-10-19</date><desc><address><country key="FR"></country></address><ref type="url">http://www.cnrs.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country><placeName><settlement type="city">Nancy</settlement><settlement type="city">Metz</settlement><region type="region" nuts="2">Grand Est</region><region type="old region" nuts="2">Lorraine (région)</region></placeName><orgName type="university">Université de Lorraine</orgName></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Load-sensing floors are capable of tracking objects without suffering from occlusions nor posing the same privacy issues as cameras. They have been mostly used to analyze human gait as a way of continuous diagnosis but could also be placed alongside robots to help monitoring in specialized institutions, such as elderly care facilities. However, large-scale deployments necessitate cheap sensors which do not necessarily offer the same precision. With more noisy sensors, lighter robots might be difficult to track and precisely localize. In this article, we investigate various models in order to estimate the position of a robot. We experiment with several robots of different weights and compare the models' estimates against ground truth measurements provided by a motion capture system. We show that with standard-sized tiles of 60 cm, we can track even the lighter robots with less than 4 cm of error.</div></front></TEI><affiliations><list><country><li>France</li><li>Suisse</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="Suisse"><noRegion><name sortKey="Rio, Maxime" sort="Rio, Maxime" uniqKey="Rio M" first="Maxime" last="Rio">Maxime Rio</name></noRegion></country><country name="France"><region name="Grand Est"><name sortKey="Colas, Francis" sort="Colas, Francis" uniqKey="Colas F" first="Francis" last="Colas">Francis Colas</name></region><name sortKey="Andries, Mihai" sort="Andries, Mihai" uniqKey="Andries M" first="Mihai" last="Andries">Mihai Andries</name><name sortKey="Charpillet, Francois" sort="Charpillet, Francois" uniqKey="Charpillet F" first="François" last="Charpillet">François Charpillet</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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