PERCEPTION
Mobile robot navigation using sensor fusion
Fernando Lizarralde, Eduardo V. L. Nunes, Liu Hsu, John T. Wen
- Year
- 2004
- Citations
- 18
Abstract
This paper considers the localization and navigation of a mobile robot. The control strategy is based on a nonlinear model predictive control technique that utilizes the Newton method. The robot localization is obtained using information from odometric and ultrasonic sensors through a Kalman filter. Simulation and experimental results illustrate the efficacy of the proposed method.
Keywords
Mobile robotKalman filterSensor fusionComputer scienceExtended Kalman filterMobile robot navigationRobotComputer visionArtificial intelligenceSimultaneous localization and mapping
Related papers
OTHER
📊 26,957 cites
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
PERCEPTION
📊 22,245 cites
Artificial intelligence: a modern approach
1995
OTHER
📊 18,993 cites
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
SWARM
📊 14,853 cites
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002