Abstract
Self-localization of a robot in an indoor plant is one of the most important requirement in mobile robotics. This paper addresses the application and improvement of a well known localization algorithm used in Robocup Midsize league competition in real service and industrial robots. This new robust approach is based on modeling the quality of several measures and minimizing the maching error. The presented innovative work applies the robotic football knowledge to other fields with high accuracy. Real and simulated results allow to validate the proposed methodology.
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References
Wulf, O., Lecking, D., Wagner, B.: Robust Self-Localization in Industrial Environmentsbased on 3D Ceiling Structures. In: Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (2006)
Liu, J., Yin, B., Liao, X.: Robot Self-localization with Optimized ErrorMinimizing for Soccer Contest. Journal Of Computers 6(7) (2011)
Quigley, M., Gerkey, B., Conley, K., Faust, J., Foote, T., Leibs, J., Berger, E., Wheeler, R., Ng, A.Y.: ROS: an open-source Robot Operating System. In: Proc. Open-Source Software workshop of the InternationalConference on Robotics and Automation, Kobe, Japan (May 2009)
Lauer, M., Lange, S., Riedmiller, M.: Calculating the perfect match: An efficient and accurate approach for robot self-localization. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds.) RoboCup 2005. LNCS (LNAI), vol. 4020, pp. 142–153. Springer, Heidelberg (2006)
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. Massachusetts Institute of Technology (2006)
Pinto, M., Moreira, A., Matos, A., Sobreira, H.: Novel 3D Matching Self-Localisation Algorithm. International Journal of Advances in Engineering & Technology 5(1), 1–12 (2012)
Schulz, H., Behnke, S.: Utilizing the structure of Field Lines for efficient Soccer Robot Localization. Advanced Robotics 26(14), 1603–1621 (2012)
Pinto, M., Paulo Moreira, A., Matos, A., Sobreira, H., Santos, F.: Fast 3D Matching Localisation Algorithm. Journal of Automation and Control Engineering 1(2), 110–115 (2013) ISSN 2301-3702
Grisetti, G., Stachniss, C., Burgard, W.: Improved Techniques for Grid Mapping with Rao-Blackwellized Particle Filters. IEEE Transactions on Robotics 23(1), 34–46 (2007)
Kohlbrecher, S., Meyer, J., von Stryk, O., Klingauf, U.: A Flexible and Scalable SLAM System with Full 3D Motion Estimation. In: Proceedings of IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), pp. 155–160. IEEE (2011)
Borenstain, J., Everett, H.R., Feng, L., Wehe, D.: Mobile Robot Positioning and Sensors and Techniques. Journal of Robotic Systems, Special Issue on Mobile Robots 14(4), 231–249
Aghamohammadi, A., Jensen, B., Siegwart, R.: Scan Alignment With Probabilistic Distance Metric. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004), Sendai, Japan, September 28-October 2, vol. 3, pp. 2191–2196 (2004)
Minguez, J., Lamiraux, F., Montesano, L.: Metric-Based Scan Matching Algorithms for Mobile Robot Displacement Estimation. In: Proc. of the IEEE International Conference on Robotics and Automation (ICRA), Barcelona, Spain, April 18-22, pp. 18–22 (2005)
Minguez, J., Lamiraux, F., Montesano, L.: Metric-Based Iterative Closest Point Scan Matching for Sensor Displacement Estimation. IEEE Transactions on Robotics (October 2006)
Migueis Pinto, M.: SLAM for 3D Map Building to be used in a Matching Localization Algorithm, PhD Electrical and Computer Engineering, Faculty Engineering of University of Porto (2012)
Gouveia, M., Paulo Moreira, A., Costa, P., Reis, L.P., Ferreira, M.: Robustness and Precision Analysis in Map-Matching based Mobile Robot Self-Localization. In: IROBOT – 14th Portuguese Conference on Artificial Intelligence, EPIA 2009, Aveiro, Portugal, October 12-15, pp. 243–253 (2009)
Ronzoni, D., Olmi, R., Secchi, C., Fantuzzi, C.: AGV global localization using indistinguishable artificial landmarks. In: IEEE International Conference on Robotics and Automation, pp. 287–292. IEEE, Shanghai (2011), doi:10.1109/ICRA.2011.5979759
Jensfelt, P., Kristensen, S.: Active Global Localization for a Mobile Robot Using Multiple Hypothesis Tracking. IEEE Transactions on Robotics and Automation 17(5) (October 2001)
Tipaldi, G.D., Braun, M., Arras, K.O.: FLIRT: Interest Regions for 2D Range Data with Applications to Robot Navigation. In: 12th Int. Symposium on Experimental Robotics (ISER 2010), New Delhi, India (2010)
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Sobreira, H., Pinto, M., Moreira, A.P., Costa, P.G., Lima, J. (2015). Robust Robot Localization Based on the Perfect Match Algorithm. In: Moreira, A., Matos, A., Veiga, G. (eds) CONTROLO’2014 – Proceedings of the 11th Portuguese Conference on Automatic Control. Lecture Notes in Electrical Engineering, vol 321. Springer, Cham. https://doi.org/10.1007/978-3-319-10380-8_58
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DOI: https://doi.org/10.1007/978-3-319-10380-8_58
Publisher Name: Springer, Cham
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