Automated and autonomous vehicles are in an intensive development phase. It is a phase
that requires a lot of modelling and experimental research. Experimental research into these …

Autonomous driving in unstructured environments is crucial for various applications,
including agriculture, military, and mining. However, research in unstructured environments …

This work is concerned with the vulnerability of a network industrial control system to cyber-
attacks, which is a critical issue nowadays. This is because an attack on a controlled process …

Thanks to their strong maneuverability and high load capacity, car-like robots with non-
holonomic constraints are often used in logistics to improve efficiency. However, it is difficult …

Model Predictive Control (MPC) algorithms typically use the classical L 2 cost function,
which minimises squared differences of predicted control errors. Such an approach has …

This work has two objectives. Firstly, it describes a novel physics-informed hybrid neural
network (PIHNN) model based on the long short-term memory (LSTM) neural network. The …

In this article, we present an efficient coding scheme for LiDAR point cloud maps. As a point
cloud map consists of numerous single scans spliced together, by recording the time stamp …

The paper proposes a new real-time motion planning technique for an autonomous mobile
robot that is able to find a collision-free path and a corresponding time-optimal trajectory …

This study presents the development and analysis of a technique for planning the
autonomous vehicle (AV) motion references using sequential optimization. The method …

In recent years, autonomous electric vehicles (A-EVs) have attracted the attention of
academia and industry. In urban mobility, this topology requires consensus to control …