Abstract
LiDAR sensors are very popular for mapping and localisation with mobile robots, yet they cannot handle harsh environments, containing smoke, fog, dust, etc. On the other hand, radar sensors can overcome these situations, but they are not able to represent an environment in the same quality as a LiDAR due to their limited range and angular resolution. In the following article, we present further results regarding SLAM involving the mechanical pivoting radar (MPR), which is a 2D high bandwidth radar scanner that was introduced in Fritsche et al. (Radar and LiDAR sensor fusion in low visibility environments, 2016, [8]). We present two strategies for fusing MPR and LiDAR data to achieve SLAM in an environment with low visibility. The first approach is based on features and requires the presence of landmarks, which can be extracted with LiDAR and MPR. The second SLAM approach is based on scan registration and requires a scan fusion between the two sensors. In the end, we show our experiments, involving real fog, in order to demonstrate, how our approaches make SLAM possible in harsh environments.
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References
Adams, M., Jose, E.: Robotic Navigation and Mapping with Radar. Artech House, Boston (2012)
Clark, S., Dissanayake, G.: Simultaneous localisation and map building using millimetre wave radar to extract natural features. In: International Conference on Robotics and Automation (1999)
Clark, S., Whyte, H.D.: The design of a high performance MMW radar system for autonomous land vehicle navigation. In: Field and Service Robotics (1998)
Detlefsen, J., Rozmann, M., Lange, M.: 94 HGZ 3-d imaging radar sensor for industrial environments. EARSeL Advances in Remote Sensing (1993)
Fankhauser, P., Hutter, M.: A universal grid map library: implementation and use case for rough terrain navigation. In: Koubaa, A. (ed.) Robot Operating System (ROS) - The Complete Reference, vol. 1. Springer, Berlin (2016)
Foessel, A., Apostolopoulos, D.D.: Short-range millimeter-wave radar perception in a polar environment. In: Institute, T.R. (ed.) Proceedings of the Field and Service Robotics Conference (1999)
Fritsche, P., Wagner, B.: Scanning techniques with low bandwidth radar for robotic mapping and localization. Lect. Notes Electr. Eng. 383, 321–335 (2016)
Fritsche, P., Kueppers, S., Briese, G., Wagner, B.: Radar and LiDAR sensorfusion in low visibility environments. In: Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (2016)
Holz, D., Behnke, S.: Sancta simplicitas on the efficiency and achievable results of SLAM using ICP-based incremental registration. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (2010)
Marck, J.W., Mohamoud, A., van Heijster, R., et al.: Indoor radar SLAM a radar application for vision and GPS denied environments. In: 2013 European Radar Conference (EuRAD), pp. 471–474. IEEE (2013)
Moravec, H., Elfes, A.: High resolution maps from wide angle sonar. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) (1985)
Pohl, N.: A dielectric lens antenna with enhanced aperture efficiency for industrial radar applications. In: 2010 IEEE Middle East Conference on Antennas and Propagation (MECAP), pp. 1–5. IEEE (2010)
Pohl, N., Jaeschke, T., Aufinger, K.: An ultra-wideband 80 GHz FMCW radar system using a SIGe bipolar transceiver chip stabilized by a fractional-N PLL synthesizer. IEEE Trans. Microw. Theory Tech. 60(3), 757–765 (2012)
Salman, R., Willms, I., Sakamoto, T., Sato, T., Yarovoy, A.: Environmental imaging with a mobile UWB security robot for indoor localisation and positioning applications. In: 2013 European Microwave Conference (EuMC), pp. 1643–1646 (2013)
Vivet, D., Checchin, P., Chapuis, R.: Localization and mapping using only a rotating FMCW radar sensor. Sensors, 13(4), 4527–4552 (2013)
Willeke, K., Baron, P., Martonen, T.: Aerosol Measurement: Principles, Techniques and Applications, vol. 6, pp. c1988–2007. Mary Ann Liebert, Inc., New York (1993)
Yamauchi, B.: Fusing ultra-wideband radar and lidar for small UGV navigation in all-weather conditions. In: Proceedings of the SPIE 7692, Unmanned Systems Technology XII (2010)
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This work has partly been supported within H2020-ICT by the European Commission under grant agreement number 645101 (SmokeBot).
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Fritsche, P., Kueppers, S., Briese, G., Wagner, B. (2018). Fusing LiDAR and Radar Data to Perform SLAM in Harsh Environments. In: Madani, K., Peaucelle, D., Gusikhin, O. (eds) Informatics in Control, Automation and Robotics . Lecture Notes in Electrical Engineering, vol 430. Springer, Cham. https://doi.org/10.1007/978-3-319-55011-4_9
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DOI: https://doi.org/10.1007/978-3-319-55011-4_9
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