Self-localisation of indoor mobile robots using multi-hypotheses and a matching algorithm

dc.contributor.author Pinto,M en
dc.contributor.author Héber Miguel Sobreira en
dc.contributor.author António Paulo Moreira en
dc.contributor.author Hélio Mendonça en
dc.contributor.author Aníbal Matos en
dc.date.accessioned 2017-12-28T12:34:27Z
dc.date.available 2017-12-28T12:34:27Z
dc.date.issued 2013 en
dc.description.abstract This paper proposes a new, fast and computationally light weight methodology to pinpoint a robot in a structured scenario. The localisation algorithm performs a tracking routine to pinpoint the robot's pose as it moves in a known map, without the need for preparing the environment, with artificial landmarks or beacons. To perform such tracking routine, it is necessary to know the initial position of the vehicle. This paper describes the tracking routine and presents a solution to pinpoint that initial position in an autonomous way, using a multi-hypotheses strategy. This paper presents experimental results on the performance of the proposed method applied in two different scenarios: (1) in the Middle Size Soccer Robotic League (MSL), using artificial vision data from an omnidirectional robot and (2) in indoor environments using 3D data from a tilting Laser Range Finder of a differential drive robot (called RobVigil). This paper presents results comparing the proposed methodology and an Industrial Positioning System (the Sick NAV350), commonly used to locate Autonomous Guided Vehicles (AGVs) with a high degree of accuracy in industrial environments. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/5097
dc.identifier.uri http://dx.doi.org/10.1016/j.mechatronics.2013.07.006 en
dc.language eng en
dc.relation 1434 en
dc.relation 5158 en
dc.relation 5157 en
dc.relation 5424 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Self-localisation of indoor mobile robots using multi-hypotheses and a matching algorithm en
dc.type article en
dc.type Publication en
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