This paper describes a fast method for segmentation of large-size long-range 3D point
clouds that especially lends itself for later classification of objects. Our approach is targeted …

As mobile robotics is gradually moving towards a level of semantic environment
understanding, robust 3D object recognition plays an increasingly important role. One of the …

This paper deals with the path-planning problem for mobile wheeled-or tracked-robot which
drive in 2.5-D environments, where the traversable surface is usually considered as a 2-D …

Segmentation is a most important intermediate step in point cloud data processing and
understanding. Covariance statistics based local saliency features from Principal …

We present an efficient graph-theoretic algorithm for segmenting a colored laser point cloud
derived from a laser scanner and camera. Segmentation of raw sensor data is a crucial first …

LiDAR panoptic segmentation is a newly proposed technical task for autonomous driving. In
contrast to popular end-to-end deep learning solutions, we propose a hybrid method with an …

The effective monitoring and maintenance of power lines are becoming increasingly
important due to a global growing dependence on electricity. The costs and risks associated …

In this paper, we propose a segment-based object detection approach using laser range
data. Our detection approach is built up of three stages: First, a hierarchical segmentation …

This letter proposes three-filters-to-normal (3F2N), an accurate and ultrafast surface normal
estimator (SNE), which is designed for structured range sensor data, eg, depth/disparity …

In this paper, we consider the problem of building 3D models of complex staircases based
on laser range data acquired with a humanoid. These models have to be sufficiently …