Map Building of Unknown Environment Using L1-norm, Point-to-Point Metric and Evolutionary Computation

 

Jaroslav Moravec

 

Czech Technical University in Prague, Prague, Czech Republic, (e-mail: j.moravec.email@seznam.cz; webpage and source code: robomap.4fan.cz, www.openslam.org).

 

Manuscript received June 20, 2012.
Manuscript accepted for publication July 24, 2012.

 

Abstract

In the present paper, a method for building a map of an unknown environment (SLAM) derived from the ICP algorithm using point-to-point metric is proposed. The polarscan matching technology is used for estimation of the robot location change between two scans in sequence estimate the correct position of the robot. Since map building is fairly time-consuming, the algorithm of differential evolution (DE) is used in the calculation. This efficient optimizer provides very good results in different types of small office environment (unstructured and structured). The new type of an algorithm for map building is based purely on simple geometric primitives— vectors and integrates the modern evolutionary algorithm—DE. The presented algorithm falls into the wider group of geometric map builders and is able to build a map of indoor, mostly office, environment without moving objects.

Key words: SLAM, robot localization, evolutionary robotics, differential evolution, L1-norm.

 

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REFERENCES

[1] P.J. Besl, and H.D. McKay, "A method for registration of 3-D shapes," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, 1992.         [ Links ]

[2] J. Brest, S. Greiner, B. Boskoviċ, M. Mernik, and V. Žumer, "Self-adapting control parameters in differential evolution: A comparative study on numerical benchmark problems," IEEE Trans. on Evolutionary Computation, vol. 10, no. 6, pp. 646-657, 2006.         [ Links ]

[3] W. Burgard, D. Fox, D. Hennig, and T. Schmidt, "Estimating the absolute position of a mobile robot using position probability grids," in Proc. of the National Conference on Artificial Intelligence, pp. 896-901, 1996.         [ Links ]

[4] A. Censi, "An ICP variant using a point-to-line metric," IEEE International Conference on Robotics and Automation ICRA 2008, pp. 19-25, 2008.         [ Links ]

[5] I.J. Cox, "Blanche - An experiment in Guidance and Navigation of an Autonomous Robot Vehicle," IEEE Trans. on Robotics and Automation, vol. 7, no. 2, pp. 193-204, 1991.         [ Links ]

[6] J.L. Crowley, "World Modeling and Position Estimation for a Mobile Robot Using Ultrasonic Ranging," International Conference on Robotics and Automation, pp. 674-680, 1989.         [ Links ]

[7] J.L. Crowley, "Dynamic World Modeling for an Intelligent Mobile Robot Using a Rotating Ultra-Sonic Ranging Device," tech. report CMU-RI-TR-84-27, Robotics Institute, Carnegie Mellon University, 1984.         [ Links ]

[8] J.L. Crowley, "Navigation for an intelligent mobile robot," IEEE Journal of robotics and automation, vol. 1, no. 1, 1985.         [ Links ]

[9] F. Dellaert, D. Fox, W. Burgard, S. Thrun, "MonteCarlo localization for mobile robots," Journal of Artificial Intelligence, vol. 128, no. 1-2, pp. 99-141, 1999.         [ Links ]

[10] R.O. Duda, P.E. Hart, Pattern Classification and Scene Analysis, Wiley-Interscience, 1976.         [ Links ]

[11] M. Ebner, "Evolving environment model for robot localization," Euro GP1999, Ebenhard-Karls-Universitat Tubingen, Germany, Springer Verlag, pp. 184-192, 1999        [ Links ]

[12] A.E. Eiben, R. Hinterding, and Z. Michalewicz, "Parameter control in evolutionary algorithms," IEEE Transaction on evolutionary computation, vol. 3, no. 2, pp. 124-141, 1999.         [ Links ]

[13] D. Fox, W. Burgard, and S. Thrun, "Markov localization for mobile robots in dynamic environments," Journal of Artificial Intelligence Research, pp. 391-427, 1999.         [ Links ]

[14] R. Gamperle, S.D. Muller, and P. Koumoutsakos, "A parameter study for differential evolution", WSEAS Int. Conference on advances in intelligent systems, pp. 293-298, 2002.         [ Links ]

[15] Q. Ke, and T. Kanade, "Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming," IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2005), 2005.         [ Links ]

[16] N.M. Kwok, D.K. Liu, and G. Dissanayake, "Evolutionary computing based mobile robot localization," Engineering Applications of Artificial Intelligence, vol. 19, pp. 857-868, 2006.         [ Links ]

[17] J.C. Latombe, and A. Lazanas, "Landmark-Based Robot Navigation," Algorítmica, vol. 13, no. 5, pp. 472-501, 1997.         [ Links ]

[18] J.J. Leonard, and H.F. Durrant-Whyte, "Simultaneous map building and localization for an autonomous mobile robot," Conference IROS-91, Osaka, Japan, pp. 1442-1447, 1991.         [ Links ]

[19] J.J. Leonard, and H. F. Durrant-Whyte, "Mobile robot localization by tracking geometric beacons," IEEE Trans. on Robotics and Automation, vol. 7, no. 3, pp. 376-382, 1991.         [ Links ]

[20] J.J. Leonard, I.J. Cox, and H.F. Durrant-Whyte, "Dynamic map building for an autonomous mobile robot," Int. journal on Robotics Research, vol. 11, no.4, pp. 286-298, 1992.         [ Links ]

[21] F. Lu, and E. Milios, "Robot pose estimation in unknown environments by matching 2D range scans," Journal of Intelligent Robotics Systems, vol. 18, no. 3, pp. 249-275, 1997.         [ Links ]

[22] E.M. Montes, and A.G.P. Ortiz, "Self-adaptive and Deterministic Parameter Control in Differential Evolution for Constrained Optimization," IEEE Congress on Evolutionary Computation, pp. 1375 - 1382, 2009.         [ Links ]

[23] H.P. Moravec, and A. Elfes, "High resolution maps from wide angle sonar," in Proc. IEEE Int. Conf. Robotics and Automation, pp. 116-121, 1985.         [ Links ]

[24] M.R. Mohammadi, and S.S. Ghidary, "Integrated PSO and line based representation approach for SLAM," in Proceedings of the 2011 ACM Symposium on Applied Computing, pp.1382-1388, 2011.         [ Links ]

[25] L. Moreno, S. Garrido, D. Blanco, and M.L. Muñoz, "Differential evolution solution to the SLAM problem," Journal of Robotics and Autonomous Systems, vol. 57, no. 4, 2009.         [ Links ]

[26] L. Moreno, J.M. Armingol, S. Garrido, A. Escalera, and M.A. Salichs, "A Genetic Algorithm for Mobile Robot Localization Using Ultrasonic Sensors," Journal of Intelligent and Robotic Systems, vol. 34, no. 2, 2002.         [ Links ]

[27] T. Pavlidis, and S.L. Horowitz, "Segmentation of Plane Curves," IEEE Trans. on Computers, vol. 23, no. 8, pp. 860-870, 1974.         [ Links ]

[28] S.T. Pfister, S.I. Roumeliotis, and J.W. Burdick, "Weighted Line Fitting Algorithms for Mobile Robot Map Building and Efficient Data Representation," ICRA 2003, pp. 14-19, 2003.         [ Links ]

[29] S.T. Pfister, "Weighted line fitting and merging," Tech. Rep., California Institute of Technology (2002), Available: http://robotics.caltech.edu/~sam/TechReports/LineFit/linefit.pdf        [ Links ]

[30] A.K. Qin, and P.N. Suganthan, "Self-adaptive differential evolution algorithm for numerical optimization," The 2005 IEEE Congress on In Evolutionary Computation, vol. 2, pp. 1785-1791, 2005.         [ Links ]

[31] A. Siadat, A. Kaske, S. Klausmann, M. Dufaut, and R Husson, "An Optimized Segmentation Method for a 2D Laser-Scanner Applied to Mobile Robot Navigation," in Proceedings of the 3rd IFAC Symposium on Intelligent Components and Instruments for Control Applications, 1997.         [ Links ]

[32] M. Schmidt, "Least Squares Optimization with L1-Norm Regularization," CS542B Project Report, 2005.         [ Links ]

[33] P. Skrzypcynsky, "Simultaneous Localization and mapping: a feature based probabilistic approach," Int. Journal of Applied Mathemahics and Computer Science, vol. 19, pp. 575-588, 2009.         [ Links ]

[34] P. Skrzypczyňski, "Building Geometrical map of environment using IR range finder data," Intelligent Autonomous Systems, U.Rembold et. al. IOS Press, 1995.         [ Links ]

[35] R. Storn, "On the Usage of Differential Evolution for Function Optimization," NAFIPS'96, pp. 519-523, 1996.         [ Links ]

[36] R. Storn, and K. Price, "Differential Evolution - a Simple and Efficient Heuristic for Global Optimization," Journal of Global Optimization, vol. 11, pp. 341-359, 1997.         [ Links ]

[37] J. Teo, "Exploring dynamic self-adaptive populations in differential evolution," Journal of Soft Computing, vol. 10, pp. 673-686, 2006.         [ Links ]

[38] C.K. Wong, J. Schmidt, and W.K. Yeap, "Using a Mobile Robot for Cognitive Mapping," International Joint Conference on Artificial Intelligence (IJCAI), Hyderabad, India, 2007.         [ Links ]

[39] W.K. Yeap, "Towards a computational theory of cognitive maps," Artificial Intelligence, vol. 34, pp. 297-360, 1988.         [ Links ]

[40] R. Kummerle, G. Grisetti, H. Strasdat, K.Konolige, and W. Burgard, "g2o: A General Framework for Graph Optimization,", in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3607-3613, 2011.         [ Links ]

[41] N. Metropolis, and S. Ulam, "The Monte Carlo method," Journal of the American Statistical Aassociation, vol. 44, 335-341, 1949.         [ Links ]

[42] D. Whitley, S. Rana, and R.B. Heckendorn, "The Island Model Genetic Algorithm: On Separability, Population Size and Convergence," Journal of Computing and Information Technology, vol. 7, pp. 33-47, 1998.         [ Links ]

[43] R. Tanese, "Distributed Genetic Algorithms," Proc. of the Third International Conference on Genetic Algorithms, MorganKaufmann, J.D.Schaffer editor, pp. 434-439, 1989.         [ Links ]

[44] M. Gorges-Schleuter, "Explicit parallelism of Genetic Algorithms through Population Structures," Paraller Problem Solving from nature, Springer Verlag, H.P. Schwefel and Reinhard Manner, editors, pp. 150-159, 1991.         [ Links ]

[45] M. Begum, G.K.I. Mann, and R.G. Gosine, "An Evolutionary Algorithm for Simultaneous Localization and Mapping of Mobile Robots," Proc. of The IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 4066-4071, 2006.         [ Links ]

[46] M. Begum, G.K.I. Mann, and R.G. Gosine, ,A Fuzzy-Evolutionary Algorithm for Simultaneous Localization and Mapping of Mobile Robots," Proc. of IEEE Congress on Evolutionary Computation, pp. 1975-1982, 2006.         [ Links ]

[47] M. Begum, G.K.I. Mann, and R.G. Gosine, ,J.ntergrated fuzzy logic and genetic algorithmic approach for simultaneous localization and mapping of mobile robots," Journal of Applied Soft Computing, vol. 8, no. 1, January, 2008.         [ Links ]

[48] D.E. Goldberg, "Simple genetic algorithms and the minimal deceptive problem," Genetic Algorithms and Simulated Annealing, London, Pitman, pp. 74-88, 1987.         [ Links ]

[49] D.E. Goldberg, "Genetic algorithms in search, optimization, and machine learning," Addison-Wesley New York, 1989.         [ Links ]

[50] K. Price, D. Corne, M. Dorigo, and F. Glover, "An Introduction to Differential Evolution," Eds. London, McGraw-Hill, pp. 79-108, 1989.         [ Links ]

[51] K. Price, and R. Storn, "Minimizing the Real Functions of the ICEC'96 contest by Differential Evolution," IEEE Int. Conference on Evolutionary Computation (ICEC'96), pp. 842-844, 1996.         [ Links ]

[52] M. Dorigo, "Optimization, Learning and Natural Algorithms", Ph.D. dissertation, Politecnico di Milano, Italy, 1992.         [ Links ]

[53] J. Kennedy, and R.C. Eberhart, "Particle swarm optimization," Proc. of the 1995 IEEE International Conference on Neural Networks, 1995.         [ Links ]

[54] J. Moravec, "Cascaded Evolutionary Estimator for Robot Localization," International Journal of Applied Evolutionary Computation (IJAEC), vol. 3, no. 3, pp. 33-61, 2012.         [ Links ]

[55] J. Moravec, "Continuous Robot Localization in Known Environment Using Genetic Algorithms," The 10th IEEE Int. Conference on Fuzzy Systems FUZZ IEEE 2001, Melbourne, Australia, p.6, 2001        [ Links ]