Environment perception, one of the most fundamental and challenging problems of
autonomous vehicles (AVs), has been widely studied in recent decades. Due to inferior fault …

The simultaneous surges in the research on socially assistive robotics and that on computer
vision can be seen as a result of the shifting and increasing necessities of our global …

Accurately estimating the current state of local traffic scenes is one of the key problems in the
development of software components for automated vehicles. In addition to details on free …

In this paper, we consider the transformation of laser range measurements into a top-view
grid map representation to approach the task of LiDAR-only semantic segmentation. Since …

We present a generic evidential grid mapping pipeline designed for imaging sensors such
as LiDAR and cameras. Our grid-based evidential model contains semantic estimates for …

Recently, 3D object detection based on multi-modal sensor fusion has been increasingly
adopted in automated driving and robotics. For example, the semantic information provided …

Accurately estimating the current state of local traffic scenes is a crucial component of
automated vehicles. The desired representation may include static and dynamic traffic …

Uncertainty about urban environments stems not only from imprecise pose estimation and
noisy information in images but also from the lack of semantic information. This article …

In motion planning for automated vehicles, a thorough uncertainty consideration is crucial to
facilitate safe and convenient driving behavior. This work presents three motion planning …

In this paper we introduce a novel way to predict semantic information from sparse, single-
shot LiDAR measurements in the context of autonomous driving. In particular, we fuse …