Abstract
Usually the Industrial Automatic Guide Vehicles (AGVs) have two kind of lasers. One for navigation on the top and others for obstacle detection (security lasers). Recently, security lasers extended its output data with obstacle distance (contours) and reflectivity, that allows the development of a novel localization system based on a security laser. This paper addresses a localization system that avoids a dedicated laser scanner reducing the implementations cost and robot size. Also, performs a tracking system with precision and robustness that can operate AVGs in an industrial environment. Artificial beacons detection algorithm combined with a Kalman filter and outliers rejection method increase the robustness and precision of the developed system. A comparison between the presented approach and a commercial localization system for industry is presented. Finally, the proposed algorithms were tested in an industrial application under realistic working conditions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wulf, O., Lecking, D., Wagner, B.: Robust self-localization in industrial environments based 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 Error Minimizing 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 International Conference 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: RoboCup Symposium, Osaka, Japan, July 13–19, 2005, pp. 142–53 (2005)
Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics. Massachusetts Institute of Technology (2006)
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)
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 (1997)
Ronzoni, D., Olmi, R., Secchi, C., Fantuzzi, C.: AGV global localization using indistinguishable artificial landmarks. In: IEEE International Conference on Robotics and Automation, Shanghai, pp. 287–292. IEEE (2011). doi:10.1109/ICRA.2011.5979759
Thrun, S., Burgard, W.: Probabilistic Robotics (Intelligent Robotics and Autonomous Agents series). The MIT Press (2005)
Eliazar, A.I., Parr, R.: Learning probabilistic motion models for mobile robots. In: Proceedings of International Conference on Machine Learning (2004)
Sobreira, H., Pinto, M., Moreira, A.P., Costa, P.G., Lima, J.: Robust robot localization based on the perfect match algorithm. In: Proceedings of the 11th Portuguese Conference on Automatic Control Lecture Notes in Electrical Engineering 2014, Portugal, vol. 321, pp. 607–616 (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Sobreira, H., Moreira, A.P., Costa, P.G., Lima, J. (2016). Mobile Robot Localization Based on a Security Laser: An Industry Scene Implementation. In: Reis, L., Moreira, A., Lima, P., Montano, L., Muñoz-Martinez, V. (eds) Robot 2015: Second Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-319-27149-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-27149-1_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27148-4
Online ISBN: 978-3-319-27149-1
eBook Packages: Computer ScienceComputer Science (R0)