Abstract
A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF) is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.
Highlights
With the development of technology, mobile robot technologies have made tremendous process
Nowadays, people have put forward higher demand of mobile robots for both functions and performances due to the increasing complex environments and tasks; traditional robots are evolving to intelligent robots
Wheeled robot localization technology has become a hotspot in robot researches
Summary
With the development of technology, mobile robot technologies have made tremendous process. We establish the robot location observation model with environmental features obtained from laser radar to locate the robot. By combining location observation model and motion model, and tracing environmental features with EKF, we realize precise localization of wheeled mobile robot. We obtain odometer and gyro data by applying Gaussian error motion model to their measured value directly. Through fusing these data, we generate predicted location. Laser radar continually matches external conditions with environmental map to obtain absolute location information. With this information, the robot can correct its location errors to overcome the increasing cumulative errors, realizing long-time precise location
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