UrbanLoco: Multi-Sensor Mapping and Localization in Urban Canyons

UrbanLoco provides a multi-sensor suite for mapping and localization in urban canyons, developed by Weisong Wen and updated in 2025. The data includes LiDAR and camera streams designed for autonomous vehicle navigation in dense city environments where GNSS signals are frequently obstructed. While the exact record count is not specified, the dataset is tailored for SLAM and mapping research.

Use Cases

• Developing SLAM algorithms using synchronized LiDAR point clouds and camera frames
• Evaluating localization performance in urban canyons with high GNSS signal interference
• Training mapping models for autonomous vehicles in dense urban environments

Strengths

• Multi-modal sensor suite including LiDAR and camera
• Targeted collection in urban canyon environments
• Designed for SLAM and localization research

Limitations

• Unknown sample size and row count
• Undefined geographic scope of the urban data
• Missing license documentation

Provenance

Source

weisongwen (GitHub)

Collection Method

Sensor-based collection from autonomous vehicle platforms

Freshness

Last updated November 2025.