Global Localisation Algorithm from a Multiple Hypotheses Set

Robotics Symposium and Latin American Robotics Symposium(2012)

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摘要
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).
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关键词
multiple hypotheses set,proposed methodology,laser range finder data,tracking routine,paper briefly,global localisation algorithm,artificial vision data,computationally light weight methodology,omni directional robot,differential traction robot,initial position,middle size,cost function,matching,mobile robots,kalman filters,tracking,robot kinematics
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