Abstract
Laser scanners are state-of-the-art devices used for mapping in service, industry, medical and rescue robotics. Although a lot of work has been done in laser-based SLAM, maps still suffer from interferences caused by objects like glass, mirrors and shiny or translucent surfaces. Depending on the surface’s reflectivity, a laser beam is deflected such that returned measurements provide wrong distance data. At certain positions phantom-like objects appear. This paper describes a specular reflectance detection approach applicable to the emerging technology of multi-echo laser scanners in order to identify and filter reflective objects. Two filter stages are implemented. The first filter reduces errors in current scans on the fly. A second filter evaluates a set of laser scans, triggered as soon as a reflective surface has been passed. This makes the reflective surface detection more robust and is used to refine the registered map. Experiments demonstrate the detection and elimination of reflection errors. They show improved localization and mapping in environments containing mirrors and large glass fronts is improved.
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References
Yang, S.W., Wang, C.C.: Dealing with laser scanner failure: mirrors and windows. In: IEEE International Conference on Robotics and Automation ICRA (2008)
Yang, S.W., Wang, C.C.: On solving mirror reflection in lidar sensing. IEEE/ASME Transactions on Mechatronics 16(2), 255–265 (2011)
Foster, P., Sun, Z., Park, J.J., Kuipers, B.: Visagge: visible angle grid for glass environments. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 2213–2220 (2013)
Käshammer, P.F., Nüchter, A.: Mirror identification and correction of 3d point clouds. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL–5/W4, 109–114 (2015)
Tatoglu, A., Pochiraju, K.: Point cloud segmentation with lidar reflection intensity behavior. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 786–790 (2012)
Blinn, J.F.: Models of light reflection for computer synthesized pictures. In: Proceedings of the 4th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1977, New York, NY, USA, pp. 192–198. ACM (1977)
Torrance, K.E., Sparrow, E.M.: Theory for off-specular reflection from roughened surfaces. J. Opt. Soc. Am. 57(9), 1105–1112 (1967)
Beckmann, P., Spizzichino, A.: The scattering of electromagnetic waves from rough surfaces. Pergamon Press (1963)
Koch, P., May, S., Schmidpeter, M., Kühn, M., Martin, J., Pfitzner, C., Merkl, C., Fees, M., Koch, R., Nüchter, A.: Multi-robot localization and mapping based on signed distance functions. In: 2015 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), March 2015. https://www.waset.org/conference/2015/03/istanbul/ICARSC
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Koch, R., May, S., Koch, P., Kühn, M., Nüchter, A. (2016). Detection of Specular Reflections in Range Measurements for Faultless Robotic SLAM. 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 417. Springer, Cham. https://doi.org/10.1007/978-3-319-27146-0_11
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DOI: https://doi.org/10.1007/978-3-319-27146-0_11
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