machine learning

Miniature Autonomy as One Important Testing Means in the Development of Machine Learning Methods for Autonomous Driving: How ML-Based Autonomous Driving Could Be Realized on a 1:87 Scale

In the current state of autonomous driving machine learning methods are dominating, especially for the envi- ronment recognition. For such solutions, the reliability and the robustness is a critical question. A “miniature autonomy” with model …

Miniaturautonomie und Echtzeitsysteme

In Tagungsband Echtzeit 2019, Springer Lecture Notes. Springer. (accepted)

Implementierung einer Tensor Processing Unit mit dem Fokus auf Embedded Systems und das Internet of Things

Machine learning is more and more applied in our everyday life, but also safety critical systems are increasingly equipped with ML procedures. This paper gives an insight into the implementation of a machine learning co-processor for embedded systems …

Modellierung eines humanbiologisch motivierten Regelungssystems zur Steuerung autonomer Fahrzeuge

In the research project FAUST at the University of Applied Sciences Hamburg driver assistance and autonomous systems are developed. The control algorithms of these systems have the ability to control them under certain conditions. If the conditions …

Bewertendes Lernen optimaler Bremspunkte in Kurvenfahrten

This work shows a way to implement an agent, capable to learn to drive a given track with a high speed. To illustrate the need of a machine learning technique, the physics and the complexity of driving a turn are shown. After this there is a …

Maschinelles Lernen zur Optimierung einer autonomen Fahrspurführung

In this work a model-free path tracking method was developed. The method considers the vehicle kinematics, the path geometry and the delayed control actions in order to determine the optimal control action. The predictive path tracking method applies …

Steuerungsoptimierung eines autonomen Fahrzeugs mittels Reinforcement Learning

Im Forschungsprojekt FAUST aus dem Department für Informatik der Hochschule für Angewandte Wissenschaften Hamburg werden Technologien für Fahrerassistenz- und Au- tonome Systeme entwickelt und entworfen (FAUST, 2010). Autonomes Fahren wurde auf …

Adaptive Choice of Grid and Time in Reinforcement Learning

We propose local error estimates together with algorithms for adap- tive a-posteriori grid and time refinement in reinforcement learn- ing. We consider a deterministic system with continuous state and time with infinite horizon discounted cost …

Multi-Grid Methods for Reinforcement Learning in Controlled Diffusion Processes

Reinforcement learning methods for discrete and semi-Markov de- cision problems such as Real-Time Dynamic Programming can be generalized for Controlled Diffusion Processes. The optimal control problem reduces to a boundary value problem for a fully …