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Unconstrained Influence Diagram Solver: Guido

Year
2007
Citations
16

Abstract

Mobile robot localization is taken into account as one of the most important topics in robotics. In this paper, the localization problem is extended to the cases in which estimating the position of multi robots is considered. To do so, the joint probabilistic data association filter (JPDAF) approach is applied for tracking the position of multiple robots. To characterize the motion of each robot, two models are used. First, a simple near constant velocity model is considered and then a variable velocity model is applied for tracking. This improves the performance when the robots change their velocity and conduct maneuvering movements. This issue gives an advantage to explore the movement of the manoeuvring objects which is common in many robotics problems such as soccer or rescue robots. Simulation results show the efficiency of the JPDAF algorithm in tracking multiple mobile robots with maneuvering movements.

Keywords

RobotMobile robotArtificial intelligenceRoboticsComputer scienceSolverPosition (finance)Tracking (education)Probabilistic logicComputer vision

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