OTHER
Localization of Mobile Robot using Particle Filter
Jeong Su Woo, Young-Joong Kim, Jeong-on Lee, Myo–Taeg Lim
- Year
- 2006
- Citations
- 41
Abstract
Localization is an important topic in mobile robots. It is essential that a mobile robot plans movement and reaches goals. In this paper, we described self-localization technique for mobile robot based on particle filtering in active beacon system. The basic method is to estimate value of position and heading of mobile robot using ultrasonic sensor as particle filter is used to eliminate process and measurement noise. Several variants of the particle filter such as SIR and RPF are introduced. These are discussed and compared with EKF for localization of mobile robot
Keywords
Mobile robotParticle filterHeading (navigation)Monte Carlo localizationComputer scienceRobotComputer visionExtended Kalman filterUltrasonic sensorArtificial intelligence
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