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Person detection is a crucial task for mobile robots navigating inhuman-populated environments. LiDAR sensors are promising for this task, thanksto their accurate depth measurements and large field of view. Two types ofLiDAR sensors exist: the 2D LiDAR sensors, which scan a single plane, and the3D LiDAR sensors, which scan multiple planes, thus forming a volume. How dothey compare for the task of person detection? To answer this, we conduct aseries of experiments, using the public, large-scale JackRabbot dataset and thestate-of-the-art 2D and 3D LiDAR-based person detectors (DR-SPAAM andCenterPoint respectively). Our experiments include multiple aspects, rangingfrom the basic performance and speed comparison, to more detailed analysis onlocalization accuracy and robustness against distance and scene clutter. Theinsights from these experiments highlight the strengths and weaknesses of 2Dand 3D LiDAR sensors as sources for person detection, and are especiallyvaluable for designing mobile robots that will operate in close proximity tosurrounding humans (e.g. service or social robot).

2D vs. 3D LiDAR-based Person Detection on Mobile Robots