Mapless Online Detection of Dynamic Objects in 3D Lidar

Understand

This paper presents a model-free, setting-independent method for online detection of dynamic objects in 3D lidar data.

• We explicitly compensate for the moving-while-scanning operation (motion distortion) of present-day 3D spinning lidar sensors.
• Our detection method uses a motion-compensated freespace querying algorithm and classifies between dynamic (currently moving) and static (currently stationary) labels at the point level.
• For a quantitative analysis, we establish a benchmark with motion-distorted lidar data using CARLA, an open-source simulator for autonomous driving research.