Research on autonomous driving in unstructured outdoor environments is less advanced
than in structured urban settings due to challenges like environmental diversities and scene …

Most advanced autonomous driving systems (ADS) today rely on the prior creation of high-
definition maps (HD maps). This process is expensive and needs to be performed frequently …

Unmanned ground vehicles (UGVs) have a huge development potential in both civilian and
military fields, and have become the focus of research in various countries. In addition, high …

This paper presents a fully automatic large-scale point cloud mapping system for low-speed
self-driving vehicles and robots operating in complicated unstructured environments. The …

During the last decades, the research endeavours on autonomous driving found great
resonance in Advanced Driver-Assistance Solutions that equipped the contemporary civilian …

This paper proposes fast and novel methods to jointly estimate the target's unknown 3D
shape and dynamics. Measurements are noisy and sparsely distributed 3D points from a …

For autonomous driving on rural or dirt roads-neither urban nor off-road-a large terrain area
needs to be estimated at high spatial resolution. However, available computing time is very …

Much research has been done on the detection and tracking of paved, preferably marked
roads. Less work is available on the detection of dirt roads. The challenge is to provide a …

Alongside a detailed knowledge about the current environment, the ego position is a major
aspect in autonomous driving. Solving the task of localization and mapping typically consists …

This paper describes a technique to perform a post-detection fusion of camera and LiDAR
data for road boundary estimation tasks. To be specific, the technique takes the road …