Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2015.14.0149

2D Grid Map Compensation Using ICP Algorithm based on Feature Points  

Hwang, Yu-Seop (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Lee, Dong-Ju (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Yu, Ho-Yun (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Lee, Jang-Myung (Department of Electronic and Electric and Computer Engineering, Pusan National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.10, 2015 , pp. 965-971 More about this Journal
Abstract
This paper suggests a feature point-based Iterative Closest Point (ICP) algorithm to compensate for the disparity error in building a two-dimensional map. The ICP algorithm is a typical algorithm for matching a common object in two different images. In the process of building a two-dimensional map using the laser scanner data, warping and distortions exist in the map because of the disparity between the two sensor values. The ICP algorithm has been utilized to reduce the disparity error in matching the scanned line data. For this matching process in the conventional ICP algorithm, pre-known reference data are required. Since the proposed algorithm extracts characteristic points from laser-scanned data, reference data are not required for the matching. The laser scanner starts from the right side of the mobile robot and ends at the left side, which causes disparity in the scanned line data. By finding the matching points between two consecutive frame images, the motion vector of the mobile robot can be obtained. Therefore, the disparity error can be minimized by compensating for the motion vector caused by the mobile robot motion. The validity of the proposed algorithm has been verified by comparing the proposed algorithm in terms of map-building accuracy to conventional ICP algorithm real experiments.
Keywords
ICP (Iterative Closet Point) algorithm; map building; mobile robot; laser scanner;
Citations & Related Records
Times Cited By KSCI : 9  (Citation Analysis)
연도 인용수 순위
1 A. Lorusso, D. Eggert, and R. Fisher, "A comparison of four algorithms for estimating 3-D rigid transformations," Proc. of the 4th British Machine Vision Conference (BMVC 1995), pp. 237-246, Sep. 1995.
2 K. S. Arun, T. S. Huang, and S. D. Blostein, "Least square fitting of two 3-d point sets," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 9, no. 5, pp. 698-700, 1987.
3 S.-Y. Jung, "SLAM based on extended Kalman filter using laser range finder for mobile robot," M.s. thesis, Pusan National University, Feb. 2010.
4 T. Tsubouch, "Nowadays trends in map generation for mobile robot," IEEE International conference on Intelligents Robots and Systems, vol. 2, pp. 828-833, 1996.
5 J. Borenstein and L. Feng, "Measurement and correction of systematic odometry errors in mobile robots," IEEE Trans on Robotics and Automation, vol. 12, no. 6, pp. 869-880, 1996.   DOI
6 K. Lee, C. Chung, and W. Chung, "Accurate calibration of kinematic parameters for two wheel differential mobile robots," Journal of Mechanical Science and Technology, vol. 25, no. 6, pp. 1603-1611, 2011.   DOI
7 Y.-K. Kwon, "A path generation method for a autonomous mobile robot based on a virtual elastic force," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 8, no. 1, pp. 149-157, 2013.   DOI
8 Y.-S. Moon, S.-H. Roh, K.-H. Jo, and Y.-C. Bae, "Robot localization and monitoring using OpenRTM in outdoor environment based on precision GPS," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 7, no. 2, pp. 425-431, 2012.   DOI
9 K.-S. Yoon, "Improved localization algorithm for ultrasonic satellite system," The Journal of the Korea Institute of Electronic Communication Sciences, vol. 6, no. 5, pp. 775-781, 2011.
10 T.-B. Kwon, J.-B. Song, and S.-C. Kang, "Extraction and matching of elevation moment of inertia for elevation mapbased localization of an outdoor mobile robot," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 15, no. 2, pp. 203-210, 2009.   DOI
11 C. Ye and J. Borenstein, "A new terrain mapping method for mobile robots obstacle negotiation," Processing of UGV Technology Conference, SPIE AeroSense Symposium, pp. 52-62, 2003.
12 J.-S. Kim, K.-H. Ahn, and C.-H. Sung, "Refinements of multisensor based 3D reconstruction using a multi-sensor fusion disparity map," Journal of Korea Robotics Society, vol. 4, no. 4, pp. 298-304, 2008.
13 S. Lee, Y. Kim, and H. Bang, "Experimental verification of multi-sensor geolocation algorithm using sequential Kalman filter," Journal of Institute of Control, Robotics and Systems, vol. 21, no. 1, pp. 7-13, 2015.   DOI
14 D. Oritin, J. Neira, and J. M. M. Montiel, "Relocation using laser and vision," IEEE international conference on Robotis and Automation, vol. 2, pp. 1505-1510, 2004.
15 S.-H. Kim, C.-W. Jho, and H.-K. Hong, "automatic registration method for multiple 3D range data sets," Journal of KISS : Software and Application, vol. 30, no. 11,12, pp. 1239-1246, 2003.
16 S. Y. Cho, "Biaxial accelerometer-based magnetic compass module calibration and analysis of azimuth computational errors caused by accelerometer errors," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 20, no. 2, pp. 149-156, 2014.   DOI
17 D. Oritin, J. Neira, and J. M. M. Montiel, "Relocation using laser and vision," IEEE international conference on Robotics and Automation, vol. 2, pp. 1505-1510, 2004.
18 T. Fuiita and Y. Kondo, "3D terrain measurement system with movable laser range finder," 2009 IEEE International workshop on (SSRR), no. 2, pp. 1-6, Nov. 2009.
19 Kazunori Ohno and Satoshi Tadokoro, "Dense 3D map building based on LRF data and color image fusion," IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2792-2797, 2005.
20 H. Surmann, K. Lingemann, A. Nuchter, and J. Hertzberg, "A 3D laser range for autonomous mobile robots," Proc. of the 32nd ISR, pp. 153-158, 19-21, Apr. 2001.
21 Y.-S. Hwang, H.-W. Kim, T.-J. Kim, and J.-M. Lee, "Impulse noise removal of LRF for 3D map building using a hybrid median filter," Journal of Institute of Control, Robotics and Systems (in Korean), vol. 18, no. 10, pp. 970-976, 2012.   DOI
22 S.-W. Noh, T.-G. Kim, and N.-Y. Ko, "Map building using ICP algorithm based a robot position prediction," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 8, no. 4, pp. 575-582, 2013.   DOI
23 P. Besl and N. McKay, "A method for registration of 3-D shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, 1992.   DOI
24 S.-W. Noh, T.-G. Kim, and N.-Y. Ko, "Map building using ICP algorithm based a robot position prediction," The Journal of The Korea Institute of Electronic Communication Sciences, vol. 8, no. 4, pp. 575-582, 2013.   DOI