Consensus Algorithms for Single-Integrator Multi-Agent Systems

In multi-agent systems reaching consensus has been a long-standing problem. A considerable amount of research has been focused on how event-triggered consensus can be used to limit the energy consumption of the communication system while still ensuring convergence to the neighbourhood of a point or a formation. These algorithms rely on having...

Sampling-Based MPC with Learning-Based Trajectory Predictions for Interaction-Aware Motion Planning: Autonomous navigation in urban canals

With the world’s population recently surpassing the 8 billion mark, population growth poses significant challenges on the planet. This growth is particularly evident in urban areas, and as a consequence, cities must find innovative ways to accommodate the increasing pressure on the current road infrastructure. In Amsterdam, a city with an...

Distributed Gaussian Process for Multi-agent Systems

This work is focused on the distributed system, i.e. Multi-agent Systems (MAS), with application in environmental monitoring and learning. The specific task is to develop algorithms, i.e. Gaussian Process (GP), that are robust, accurate and fully-distributed to learn the unknown spatial environmental field. The two main problems are (1). how to...

Dynamic improvement of robustness of power transmission grids in decentralized and distributed environments

Power transmission networks are large scale complex distributed and networked systems, situated in dynamic environments. Managing such systems is essentially decentralized and distributed. The main function of power transmission grids is to assure the security and reliability of the network and to avoid blackouts. Key elements that can determine...