In the current Big Data era, large amounts of data are collected from complex systems, such as sensor networks and social networks. The emerging field of graph signal processing (GSP) leverages a network structure (graph) to process signals on an irregular domain. This thesis studies the forecasting of multi-dimensional graph processes, i.e., where each entity in the network carries a multivariate time series. Recent research has proposed to use product graphs to model the dependencies between different variables in multi-dimensional graph processes and employ them in graph-based vector autoregressive models to predict future values. A problem with these product graph-based models is that they can be too restrictive. In this work, it is proposed to combine product graph-based models with multiple one-dimensional models to implement more estimation flexibility. To further increase the degrees of freedom, the use of multiple-input-multiple-output graph filters is also proposed. The proposed models are implemented and tested on synthetic and real-world data sets, which shows an improved forecasting performance compared to state-of-the-art alternatives.

The Zebro is a six legged autonomous robot, designed to be deployed in swarms. Charging the battery is still done manually. To further increase the autonomous abilities of the Zebro, a wireless charging station and module is designed. The charging station is fully modular and interconnected by charging pads. This opens the possibility of charging multiple Zebro's simultaneously. The charging module consists of a receiver and Battery Management System inside the Zebro. In this thesis, both the transmitter and receiver side of the Wireless Power Transfer (WPT) system is designed. The transmitter and receiver must be perfectly aligned for high efficiency in a wireless charging setup. The positioning of the Zebro is not highly accurate, therefore the design of an inductive WPT system using SS-topology compensation is presented. Also, possible solutions improving the efficiency of the power transfer and the WPT system is proposed in this thesis. These improvements include coil optimization, object detection, circuit damage protection and implementation into the overall system.