In this paper, two new algorithms for feature detection are presented. The flrst one can detect edge and circle features accurately using the Gaussian-Newton optimization method to flt the circle parameters. It consists of two parts: the flrst is the segmentation of data of each scan which is followed by parameter acquisition. The algorithm is ofi-line in nature as the segmentation and parameter acquisition are carried out after each scan data is collected. We also present another algorithm which is on-line and applies a multiple models flltering approach to handle features of difierent geometries such as lines and circles. It detects the circle features using the unscented Kalman fllter. Experimental results show that the proposed two approaches are e-cient in detecting features.
In REF were tested two methods for circle detection: an on-line method using the unscented Kalman lter; and an off-line method using Gaussian-Newton optimization of the circle parameters.
Geometrical Feature Extraction Using 2D Range Scanner
2003 4th International Conference on Control and Automation Proceedings
2003 4th International Conference on Control and Automation Proceedings
Computer Science