What question did this study set out to answer?

The aim is to design efficient person detection algorithms utilizing LiDAR sensors for mobile robots.

February 27, 2026Open Access

Efficient person detection with LiDAR sensors for mobile robots

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Thesis demonstrates enhanced person detection in mobile robots using LiDAR, suggesting efficient sensor implementation.

The aim is to design efficient person detection algorithms utilizing LiDAR sensors for mobile robots.
Developed DR-SPAAM, a person detection algorithm for 2D LiDAR sensors.
Created pseudo-labels from calibrated camera and image-based detector to improve training.
Implemented Global Hierarchical Attention for efficient processing of point clouds.
DR-SPAAM achieved 70.3% AP on the DROW dataset with 87.2 FPS on a dedicated GPU.
Pseudo-label training significantly enhanced detection performance and generalization.
Comparison showed 2D LiDAR detection accuracy on par with 3D LiDAR for visible persons.

Dan Jia (2025) studied this question.

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February 27, 2026Open Access

View Full Paper

Ask AI

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Authors

Thesis demonstrates enhanced person detection in mobile robots using LiDAR, suggesting efficient sensor implementation.

The aim is to design efficient person detection algorithms utilizing LiDAR sensors for mobile robots.
Developed DR-SPAAM, a person detection algorithm for 2D LiDAR sensors.
Created pseudo-labels from calibrated camera and image-based detector to improve training.
Implemented Global Hierarchical Attention for efficient processing of point clouds.
DR-SPAAM achieved 70.3% AP on the DROW dataset with 87.2 FPS on a dedicated GPU.
Pseudo-label training significantly enhanced detection performance and generalization.
Comparison showed 2D LiDAR detection accuracy on par with 3D LiDAR for visible persons.

Dan Jia (2025) studied this question.

View Full Paper

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