One of the biggest boosts for innovation in engineering has been the ongoing improvement
of digital processor technology. Connections between physical systems and computing …

Enhanced logistics is widely regarded as a key technology to increase flexibility and cost
efficiency of today's factories. For example, fully autonomous transport vehicles aim to …

Motion planning algorithms for urban automated driving must handle uncertainty due to
unknown intention and future motion of Dynamic Obstacles (DOs). Considering a single …

In motion planning for autonomous racing, the challenge arises in planning smooth
trajectories close to the handling limits of the vehicle with a sufficient planning horizon …

Autonomous driving in urban environments depends on the ability to interpret the current
situation and to react accordingly. This means to continuously make decisions for certain …

Durch den Einsatz autonomer Fahrzeuge kann der Straßenverkehr effizienter, komfortabler
und vor allem sicherer gestaltet werden. Neben der hierfür erforderlichen …

In this paper we propose a Reinforcement Learning (RL) algorithm for path tracking of a real
car-like robot. The RL network is trained in simulation and then evaluated on a small racing …

Trajectory planning for autonomous driving is challenging because the unknown future
motion of traffic participants must be accounted for, yielding large uncertainty. Stochastic …

The paper introduces a novel general feedback control framework, which allows applying
the motion controllers originally dedicated for the unicycle model to the motion task …

Knowing the course of the road, together with the corresponding road boundaries is an
essential component of many advanced driver-assistance systems and of autonomous …