Publication
GSeg3D: A High-Precision Grid-Based Algorithm for Safety-Critical Ground Segmentation in LiDAR Point Clouds
Haider Khan Lodhi; Christoph Hertzberg
In: 2025 7th International Conference on Robotics and Computer Vision (ICRCV). International Conference on Robotics and Computer Vision (ICRCV-2025), October 24-26, Hong Kong, China, Hong Kong, IEEE, 2025.
Abstract
Ground segmentation in point cloud data is the process of separating ground points from non-ground points. This task is fundamental for perception in autonomous driving and robotics, where safety and reliable operation depend on the precise detection of obstacles and navigable surfaces. Existing methods often fall short of the high precision required in safety-critical environments, leading to false detections that can compromise decision-making. In this work, we present a ground segmentation approach designed to deliver consistently high precision, supporting the stringent requirements of autonomous vehicles and robotic systems operating in real-world, safety-critical scenarios.