A Real-Time SLAM Algorithm Based on EKF for Field Robot
Date Issued
2011
Date
2011
Author(s)
Liu, Chang-Chih
Abstract
In this thesis, an autonomous mobile robot applied to agricultural environment is proposed. To explore the unknown field and navigate with map, the system use SLAM algorithm and the auto path planning technique. Instead of particle filter which costs more time at calculate, our research focus on EKF-based SLAM. Depending on the theory of Kalman filter, all the error (including the motion model and measurement model) follow the Gaussian distribution. The system is equipped with the two-dimensional laser range finder to get the data, and extracts line feature and the corner feature (using Harris corner detection and the beam model of laser) from the contour of environment. Field D* lite algorithm is the main part of the navigation system. It can update the path when the map is changed in real time. The error in localization is less than 9 %, and the average running time is 1.26 seconds per step. Excluding the mapping step, the average running time is speed up to 0.45 seconds per step. With the procedure for SLAM, the average speed is 5.2cm/s. With the procedure for auto navigation, the average speed is 7.5cm/s. The result is feasible for agricultural applications.
Subjects
EKF SLAM
field robot
Type
thesis
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