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Fusing LiDAR and Radar Data to Perform SLAM in Harsh Environments

  • Paul Fritsche
  • Simon Kueppers
  • Gunnar Briese
  • Bernardo Wagner
Chapter
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 430)

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.

Keywords

Radar LiDAR Sensor fusion SLAM Mobile robots 

Notes

Acknowledgements

This work has partly been supported within H2020-ICT by the European Commission under grant agreement number 645101 (SmokeBot).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Paul Fritsche
    • 1
  • Simon Kueppers
    • 2
  • Gunnar Briese
    • 2
  • Bernardo Wagner
    • 1
  1. 1.Institute of Systems Engineering - Real Time Systems GroupLeibniz Universität HannoverHannoverGermany
  2. 2.Fraunhofer Institute for High Frequency Physics and Radar Techniques FHRWachtbergGermany

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