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A new localization method for mobile robot by data fusion of vision sensor data and motion sensor data

Tae-jae Lee, Wook Bahn, Byung-moon Jang, Ho-Jeong Song, Dong‐il Cho

Year
2012
Citations
9

Abstract

This paper presents a new localization method by the data fusion of vision sensor and motion sensor measurements, which can be used for mobile robots. The developed system estimates the orientation, position and velocity of a mobile robot. This is achieved by using data from a camera, robot wheel encoders, an accelerometer, and a gyroscope. The developed system is a multi-rate sampled data system. For the accurate estimation of robot position and velocity, the developed method detects the slip of robot wheels, by comparing the data from the encoders and the accelerometer. The developed method estimates the robot orientation and position by using an extended Kalman filter. The experiments are performed to verify the localization performance of the developed method in several motion scenarios, including a normal operation mode, a wheel slip mode, and a kidnap mode.

Keywords

Computer visionSensor fusionMobile robotGyroscopeArtificial intelligenceAccelerometerKalman filterComputer scienceRobotEncoder

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