Projects

There is an abundance of sensory information being collected by sensors since the emergence of the Internet of things. Combining this information (sensor fusion) to get a meaningful picture of the system under observation currently needs a lot of expert knowledge and human engineering, which doesn't scale well with the growing amount of sensors available. These sensors can vary strongly (multi-modality), ranging from complex depth camera's to ...

Autonomous vessels for inland waterways will provide a solution to multitude of socio-economic problems. While the inland shipping sector suffers from an outflow of shippers and a lack of investment in new vessels resulting in the use of old-fashioned barge designs, a sustainable solution needs to be found for the ever increasing logistical transport sector e.g. Europe expects a 50% growth of cargo in EU ports by 2030. This outflow of labour ...

Autonomous vehicles play an increasingly important role in our nowadays society. For these, accurate position and attitude estimation is crucial. This is achievable with RTK-GNSS (real-time kinematic Global Navigation Satellite System), which relies on a set of satellite measurements from both an antenna on the vehicle and a reference GNSS receiver in the vicinity. The high accuracy of this sensor is affected when nearby vegetation or ...

Hyperspectral data are widely used for various tasks, but often suffer from quality issues. Meanwhile, fusion of information gathered from multiple sources is also important for scene understanding. The goal of the research is joint image quality improvement and scene understanding using a combination of deep learning methods and classical video processing solutions. The result will be a flexible and extensible HSI restoration and sensor ...

In this PhD we develop new methods to enable deep learning neural networks to use a combination of data of different nature as input. In contrast to classic image processing CNNs, that only take video data as input, we study the possibilities of adding other sensor data to the same neural network architecture, with the aim to yield an improved accuracy. We will develop and compare novel architectures and fusing methods and evaluate it against ...

Due to the movement towards greener industries and lower operating costs there is renewed interest in transporting goods using inland waterways. However, labour expenditures currently make up about 30% of operational costs. Making the ships autonomous would therefore significantly reduce costs. However, autonomous inland waterway navigation requires very accurate localisation, due to the confined spaces of inland waterways. A common solution ...

This research aims to combine measurements from easily accessible locations on dynamic systems with multi-physical models, with a particular focus on mechatronic drivetrain applications. The goal is to obtain the best possible estimates of system states, and to enable input estimation and identification of relevant parameters. To achieve this, common sensors like accelerometers will be combined with fiber optic technology and physical models ...