Abstract:A natural landmark extraction method based on 2D laser rangefinder is described.The framework consists of three main parts: data clustering,filtering and feature extraction.According to the scale space theory in computer graphics,a curve-based estimator is developed using UKF(unscented Kalman filter),and the scan point topology describing the local environment is estimated.The filtering convolution kernel is constructed with the Mahalanobis distances obtained during estimation,and adaptive filtering of the original range image is achieved.Clustered data is segmented and characterized by the curvature function of the range data.This method is robust to noise,and can reliably extract natural landmarks in unstructured environments.Experimental results show that the proposed method is efficient in natural-landmark extraction,which can provide plenty landmarks for navigation system of autonomous mobile robot.
[1] Iyengar S,Elfes A.Autonomous mobile robots[M].Piscataway,NJ,USA:IEEE,1991.
[2] Jensfelt P,Christensen H I.Laser based pose tracking[C]//IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,1999:2994-3000.
[3] Cox I J.Blanche-An experiment in guidance and navigation of an autonomous robot vehicle[J].IEEE Transactions on Roboticsand Automation,1991,7(2):193-204.
[4] Nguyen V,Martinelli A,Tomatis N,et al.A comparison of line extraction algorithms using 2D laser rangefinder for indoor mobile robotics[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems.Piscataway,NJ,USA:IEEE,2005:1929-1934.
[5] Fang X W,Guo S,Li X H,et al.Robust mobile robot localization by tracking natural landmarks[C]//International Conference on Artificial Intelligence and Computational Intelligence.Berlin,German:Springer,2009:278-287.
[6] Again D,Dinstein I.Geometric separation of partially overlapping nonrigid objects applied to automatic chromosome classification[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1997,19(11):1212-1222.
[7] Liu H D,Srinath M D.Partial shape classification using contour matching in distance transformation[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(11):1072-1079.
[8] Nunez P,Vazquez-Martin R,del Toro J C,et al.Feature extraction from laser scan data based on curvature estimation for mobile robotics[C]//IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2006:1167-1172.
[9] Madhavan R,Durrant-Whyte H F.Natural landmark-based autonomous vehicle navigation[J].Robotics and Autonomous Systems,2004,46(2):79-95.
[10] Zhang S,Xie L H,Adams M,et al.Geometrical feature exraction using 2D range scanner[C]//International Conference on Control and Automation.Piscataway,NJ,USA:IEEE,2003:901-905.
[11] Arras K O,Tomatis N,Jensen B T,et al.Multisensor on-thefly localization:Precision and reliability for applications[J].Robotics and Autonomous Systems,2001,34(2/3):131-143.
[12] Saint-Marc P,Chen J S,Medioni G.Adaptive smoothing:A general tool for early vision[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1991,13(6):514-529.
[13] Juliet S J,Uhlmann J K,Durrant-Wbyte H F.A new method for the nonlinear transformation of means and covariances in filters and estimators[J].IEEE Transactions on Automatic Control,2000,45(3):477-482.
[14] Julier S J,Uhlmann J K,Durrant-Whyte H F.A new approach for filtering nonlinear systems[C]//American Control Conferences.Piscataway,NJ,USA:IEEE,1995:1628-1632.
[15] Perona P,Malik J.Scale-space and edge detection using anisotropic diffusion[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,1990,12(7):629-639.
[16] Knieriemen T,von Puttkamer E,Roth J.Extracting lines,circular segments and clusters from radar pictures in real time for an autonomous mobile robot[C]//IEEE Workshop on Real Time Systems.Piscataway,NJ,USA:IEEE,1991:127-135.