Abstract
In this chapter, we address the problem of aligning two partially overlapping two-dimensional maps represented by data sets acquired using range sensors. The measured data may be incomplete and noisy. To solve this problem, we used a genetic algorithm for minimizing an alignment error. A lookup-based fitness function was devised. The considered range devices are laser and focalized ultrasonic scanners. Scan matching is often considered for mobile robot displacement and/or pose estimation tasks. We experimentally show that the algorithm is robust against noise and incomplete measurements and that it can be used for both the mentioned tasks. Moreover, the proposed algorithm is suitable for both local and global robot pose estimation. Experimental results related to the convergence, accuracy and speed of the proposed algorithm with different coding approaches are reported. We compare our approach with other scan matching algorithms proposed in the literature, and we show that our approach is faster and more accurate than the others.
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References
Besl, P., McKay, N.: A method for registration of 3d shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2), 239–256 (1992)
Yamany, S., Ahmed, M., Farag, A.: A new genetic based technique for matching 3d curves and surfaces. Pattern Recognition 32, 1817–1820 (1999)
Lu, F., Milios, E.: Robot pose estimation in unknown environments by matching 2d range scans. Journal of Intelligent and Robotic Systems 18, 249–275 (1997)
Mumolo, E., Lenac, K., Nolich, M.: Spatial map building using fast texture analysis of rotating sonar sensor data for mobile robots. International Journal of Pattern Recognition and Artificial Intelligence 19(1), 1–20 (2005)
Lingemann, K., Surmann, H., Nuchter, A., Hertzberg, J.: Indoor and outdoor localization for fast mobile robots. In: Proc. of the 2004 IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS), vol. 3, pp. 2185–2190 (2004)
Cox, I.: BLANCHE: An experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transactions on Robotics and Automation 7(2), 193–204 (1991)
Biber, P., Strasser, W.: The normal distributions transform: A new approach to laser scan matching. In: Proc. of the 2003 IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS), vol. 3, pp. 2743–2748 (2003)
Chen, Y., Medioni, G.: Object modelling by registration of multiple range images. Image and Vision Computing 10, 145–155 (1992)
Zhang, Z.: Iterative point matching for registration of free-form curves. Technical report, INRIA Tech. Rep. 1658 (1992)
Pfister, S., Kriechbaum, K., Roumeliotis, S., Burdick, J.: Weighted range sensor matching algorithms for mobile robot displacement estimation. In: Proc. of the 2002 IEEE Int. Conference on Robotics and Automation (ICRA), pp. 1667–1674 (2002)
Hahnel, D., Schulz, D., Burgard, W.: Map building with mobile robot in populated environment. In: Proc. of the 2002 IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS), vol. 1, pp. 496–501 (2002)
Weiss, G., Wetzler, G., von Puttkamer, E.: Keeping track of position and orientation of moving indoor systems by correlation of range-finder scans. In: Proc. of the 1994 IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS), vol. 1, pp. 595–601 (1994)
Konolige, K., Chou, K.: Markov localization using correlation. In: Proc. of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI), pp. 1154–1159 (1999)
Thrun, S., Burgard, W., Fox, D.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3d mapping. In: Proc. of the 2000 IEEE Int. Conference on Robotics and Automation (ICRA), pp. 321–328 (2000)
Neugebauer, P.: Geometrical cloning of 3d objects via simultaneous registration of multiple range images. In: IEEE International Conference on Shape Modeling and Applications, pp. 130–139 (1997)
Fitzgibbon, A.: Robust registration of 2d and 3d point sets. In: Conference on British Machine Vision, pp. 411–420 (2001)
Rusinkiewicz, S., Levoy, M.: Efficient variants of the icp algorithm. In: 3rd International Conference on 3D Digital Imaging and Modelling, pp. 145–152 (2001)
Agrawal, A., Ansari, N., Hou, E.: Evolutionary programming for fast and robust point pattern matching. In: Proc. of the 1994 IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS), vol. 3, pp. 1777–1782 (1994)
Blais, G., Levine, M.: Registering multiview range data to create 3d computer objects. IEEE Transaction on Pattern Analysis and Machine Intelligence 17, 820–824 (1995)
MartÃnez, J.: Mobile robot self-localization by matching successive laser scans via genetic algorithms. In: 5th IFAC International Symposium on Intelligent Components and Instruments for Control Applications, pp. 1–6 (2003)
Martinez, J., Gozales, J., Morales, J., Mandow, A., Garcia-Cerezo, A.: Mobile robot motion estimation by 2d scan matching with genetic and iterative closest point algorithms. Journal of Field Robotics 23(1), 21–34 (2006)
Silva, L., Bellon, O.P., Boyer, K.: Enhanced, robust genetic algoritm for multiview range image registration. In: 4th Int. Conference on 3D digital imaging and modeling, pp. 268–275 (2003)
Lomonosov, E., Chetverikov, D., Ekart, A.: Pre-registration of arbitrarily oriented 3d surfaces using a genetic algorithm. Pattern Recognition Letters, Special Issue on Evolutionary Computer Vision and Image Understanding 27, 1201–1208 (2006)
Lenac, K., Mumolo, E., Nolich, M.: Fast genetic scan matching using corresponding point measurements in mobile robotics. In: EVOIASP 2007 European Workshop on Evolutionary Computation in Image Analysis and Signal Processing, pp. 375–382. Springer, Heidelberg (2007)
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Lenac, K., Mumolo, E., Nolich, M. (2009). Fast Genetic Scan Matching in Mobile Robotics. In: Cagnoni, S. (eds) Evolutionary Image Analysis and Signal Processing. Studies in Computational Intelligence, vol 213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01636-3_8
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DOI: https://doi.org/10.1007/978-3-642-01636-3_8
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