The purposes of this paper are to solve the low-efficiency problem caused by large search space in global localization and develop an efficient global localization method requiring only one 2D-LiDAR scan to match against the prior map for indoor mobile robots.
This paper solves the global localization problem using phase correlation as the underlying registration method. To obtain accurate rotation parameter, this paper exhaustively pre-rotates the prior map by a certain angle stride in advance. Then the input scan is matched against the pre-rotated maps one by one using phase correlation to determine translation parameters, and this paper constructs an orientation histogram by the correlation coefficients. The map rotation angle and corresponding translation parameters of the maximal peak value in the orientation histogram constitute the global pose. This paper applies a divide-and-conquer method to reduce the time consumption of single phase correlation and determines promising angle ranges where the maximal peak value may appear based on the periodicity of 90º in the orientation histogram with the signal-to-noise ratio (SNR) to reduce execution times of phase correlation.
Both simulated and real experimental results reveal that the proposed method achieves a high enough success rate and efficient (processing time in a second) global localization.
The proposed method constructs an orientation histogram to improve the global localization success rate and applies a divide-and-conquer method with SNR to improve efficiency, which will benefit the indoor mobile robots equipped with 2D-LiDAR.
