TY - GEN
T1 - A comparative analysis of radar and lidar sensing for localization and mapping
AU - Mielle, Malcolm
AU - Magnusson, Martin
AU - Lilienthal, Achim J.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/9
Y1 - 2019/9
N2 - Lidars and cameras are the sensors most commonly used for Simultaneous Localization And Mapping (SLAM). However, they are not effective in certain scenarios, e.g. when fire and smoke are present in the environment. While radars are much less affected by such conditions, radar and lidar have rarely been compared in terms of the achievable SLAM accuracy. We present a principled comparison of the accuracy of a novel radar sensor against that of a Velodyne lidar, for localization and mapping. We evaluate the performance of both sensors by calculating the displacement in position and orientation relative to a ground-truth reference positioning system, over three experiments in an indoor lab environment. We use two different SLAM algorithms and found that the mean displacement in position when using the radar sensor was less than 0.037 m, compared to 0.011 m for the lidar. We show that while producing slightly less accurate maps than a lidar, the radar can accurately perform SLAM and build a map of the environment, even including details such as corners and small walls.
AB - Lidars and cameras are the sensors most commonly used for Simultaneous Localization And Mapping (SLAM). However, they are not effective in certain scenarios, e.g. when fire and smoke are present in the environment. While radars are much less affected by such conditions, radar and lidar have rarely been compared in terms of the achievable SLAM accuracy. We present a principled comparison of the accuracy of a novel radar sensor against that of a Velodyne lidar, for localization and mapping. We evaluate the performance of both sensors by calculating the displacement in position and orientation relative to a ground-truth reference positioning system, over three experiments in an indoor lab environment. We use two different SLAM algorithms and found that the mean displacement in position when using the radar sensor was less than 0.037 m, compared to 0.011 m for the lidar. We show that while producing slightly less accurate maps than a lidar, the radar can accurately perform SLAM and build a map of the environment, even including details such as corners and small walls.
UR - http://www.scopus.com/inward/record.url?scp=85074389854&partnerID=8YFLogxK
U2 - 10.1109/ECMR.2019.8870345
DO - 10.1109/ECMR.2019.8870345
M3 - Conference contribution
AN - SCOPUS:85074389854
T3 - 2019 European Conference on Mobile Robots, ECMR 2019 - Proceedings
BT - 2019 European Conference on Mobile Robots, ECMR 2019 - Proceedings
A2 - Preucil, Libor
A2 - Behnke, Sven
A2 - Kulich, Miroslav
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 European Conference on Mobile Robots, ECMR 2019
Y2 - 4 September 2019 through 6 September 2019
ER -