Lyapunov Stable Path Planning and Control for Autonomous Vehicles

In modern society cars are one of the most important means of transportation. Unfortunately, many people die in car accidents around the world. Research shows that the number of fatal casualties in car accidents has been increasing for the past decade and that the largest cause of these accidents is the human driver. For this reason, research on...

Prioritized Experience Replay based on the Wasserstein Metric in Deep Reinforcement Learning: The regularizing effect of modelling return distributions

This thesis tests the hypothesis that distributional deep reinforcement learning (RL) algorithms get an increased performance over expectation based deep RL because of the regularizing effect of fitting a more complex model. This hypothesis was tested by comparing two variations of the distributional QR-DQN algorithm combined with prioritized...

LMI-based Stability Analysis for Learning Control: Deep Neural Networks and Locally Weighted Learning

Learning capabilities are a key requisite for an autonomous agent operating in dynamically changing and complex environments, where pre-programming is not anymore possible. Furthermore, it is essential to guarantee that the learning agent will act safely by considering its stability properties. In this thesis, novel conditions are proposed,...

Development of a Robust Reference Path Generator for Lateral Vehicle Control

Automated vehicle control provides advantages in transport efficiency, redundancy, human-safety, flexibility, and parallelism. Extensive research has been dedicated to direct-following lateral control methods, using a single preview point as reference signal. However, these methods give rise to significant tracking errors. As alternative to a...

Socially-Aware Navigation: Guiding Behavior with Pepper

Socially-aware robot navigation strives to find efficient methods to autonomously navigate known environments while incorporating social metrics derived from human behavior. Several methods built for navigation on dynamic and uncertain environments have been adapted to resemble human navigation, but fail to appropriately reflect the social...