Title :
Global Localisation Algorithm from a Multiple Hypotheses Set
Author :
Pinto, Miguel ; Sobreira, Héber ; Moreira, A. Paulo ; Mendonça, Hélio
Author_Institution :
Fac. of Eng., Univ. of Porto, Porto, Portugal
Abstract :
In this paper, a new fast and computationally light weight methodology is proposed to pinpoint a robot in a structured scenario. The localisation algorithm performs a tracking routine to pinpoint the robot´s position as it moves in a known map. To perform such tracking routine, it is necessary to know the initial position of the vehicle. This paper briefly describes the tracking routine and presents a solution to pinpoint that initial position in an autonomous way. Experimental results on the performance of the proposed methodology are presented in this paper in two different scenarios: (1) in the Middle Size Soccer Robotic League (MSL), with artificial vision data from an omni directional robot, and (2) in an indoor environment with a Laser Range Finder data from a differential traction robot (called Robot Vigil).
Keywords :
laser ranging; mobile robots; multi-robot systems; robot vision; service robots; tracking; MSL; RobotVigil; artificial vision data; autonomous robot position tracking; differential traction robot; global localisation algorithm; indoor environment; laser range finder data; middle-size soccer robotic league; multiple hypothesis set; omnidirectional robot; vehicle position tracking; Cost function; Kalman filters; Robot kinematics; Robot sensing systems; Vehicles; Matching; Middle Size League; Robot localisation; Service Robots;
Conference_Titel :
Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), 2012 Brazilian
Conference_Location :
Fortaleza
Print_ISBN :
978-1-4673-4650-4
DOI :
10.1109/SBR-LARS.2012.29