mlsanityData to 7 Oct 2026

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

arXiv 2106.11239 ↗First posted 21 Jun 2021cs.RO cs.CVcited by 6

Not on the map. Why?

Abstract (arXiv)

Person detection is a crucial task for mobile robots navigating in human-populated environments. LiDAR sensors are promising for this task, thanks to their accurate depth measurements and large field of view. Two types of LiDAR sensors exist: the 2D LiDAR sensors, which scan a single plane, and the 3D LiDAR sensors, which scan multiple planes, thus forming a volume. How do they compare for the task of person detection? To answer this, we conduct a series of experiments, using the public, large-scale JackRabbot dataset and the state-of-the-art 2D and 3D LiDAR-based person detectors (DR-SPAAM and CenterPoint respectively). Our experiments include multiple aspects, ranging from the basic performance and speed comparison, to more detailed analysis on localization accuracy and robustness against distance and scene clutter. The insights from these experiments highlight the strengths and weaknesses of 2D and 3D LiDAR sensors as sources for person detection, and are especially valuable for designing mobile robots that will operate in close proximity to surrounding humans (e.g. service or social robot).

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 35 of its 59 references that are in the map. First posted on arXiv 21 Jun 2021.

Builds on

35 of 59 references.

References · 35

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23 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1; 2025: 0; 2026: 3.

6 papers.

  1. 2021Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Networkcited by 4
  2. 2023The Un-Kidnappable Robot: Acoustic Localization of Sneaking Peoplecited by 2
  3. 2024Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Modulecited by 0
  4. 2026A Comparative Study of 3D Person Detection: Sensor Modalities and Robustness in Diverse Indoor and Outdoor Environmentscited by 0
  5. 2026ICPR 2026 Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera (TVRID)cited by 0
  6. 2026Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimizationcited by 0