Decentralized Control of Multi-Agent Dynamic Games

Recent studies in game-theory provided ways to steer multi-agent games to their Nash equilibrium by means of a decentralized approach. However, these approaches have not considered the internal dynamics of the individual agents. This thesis work provides decentralized control methods to account for these internal dynamics whilst ensuring that...

Development of a Detection and Tracking of Moving Vehicles system for 2D LIDAR sensors

The main objective of this thesis was the development and evaluation of a Detection and Tracking of Moving Objects (DATMO) system, that is capable of reliably tracking nearby vehicles from a moving car. The developed system takes in raw 2D LIght Detection And Ranging (LIDAR) measurements as input and detects objects of interest by clustering...

Iterative Bias Estimation for an Ultra-Wideband Localization System

Three bias estimation frameworks are presented that mitigate position-dependent ranging errors often present in ultra-wideband localization systems. State estimation and control are integrated, such that the positioning accuracy improves over iterations. The frameworks are experimentally evaluated on a quadcopter platform. Two state augmentation...

Smart Charging Even Smarter: Using Predictions to Increase Performance of a Cloud-Based Smart Charging Algorithm

Electric Vehicles (EVs) are considered a promising solution when it comes to reducing CO2 emissions in the transport sector. To accommodate for large numbers of EVs, a considerable amount of additional charging infrastructure must be installed. Simultaneous charging of large quantities of EVs leads to peak loads in the energy grid. One way to...

Distributed power consensus algorithm in DC microgrids

Energy distribution systems are undergoing rapid change in terms of energy generation techniques and network topology. The shift towards sustainable energy generation leads to distributed energy networks, thereby replacing the old-fashioned centralized networks. A promising type of distributed network is the microgrid. A distributed topology has...

Multi-Agent Deep Reinforcement Learning for Automated Highway Driving

Recent advances in Deep Reinforcement Learning have sparked new interest in many different research topics, including Automated Highway Driving where agents model autonomous vehicles. The main advantage of Deep Reinforcement Learning is that the training algorithm is adaptable to its environment. In highway driving, researchers often simplify...

Situational Awareness for Autonomous Interception Of Piracy Vessels Using Unmanned Surface Vessel

Globally, a growing number of kidnappings executed by pirates occur each year. The current protection consists of mercenaries which are flown in by helicopter to protect merchant ships in threat areas. This is not only expensive, sometimes innocent fishermen are seen for pirates, in some cases with a lethal ending for the fishermen. An...