In the first part, this article presents an overview of Guidance, Navigation and Control (GNC)
methodologies developed for space manipulators to perform in-orbit robotic missions …

The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

Model predictive control (MPC) theory has gained attention with the recent increase in the
processing power of computers that are now able to perform the needed calculations for this …

High-precision trajectory tracking is fundamental in robotic manipulation. While industrial
robots address this through stiffness and high-performance hardware, compliant and cost …

This paper introduces a learning-based robust control algorithm that provides robust stability
and performance guarantees during learning. The approach uses Gaussian process (GP) …

This paper presents a Learning‐based Nonlinear Model Predictive Control (LB‐NMPC)
algorithm to achieve high‐performance path tracking in challenging off‐road terrain through …

In this paper, we have developed a novel visual servo-based model predictive control
method to steer a wheeled mobile robot (WMR) moving in a polar coordinate toward a …

A novel learning Model Predictive Control technique is applied to the autonomous racing
problem. The goal of the controller is to minimize the time to complete a lap. The proposed …

Motivated by vision-based control of autonomous vehicles, we consider the problem of
controlling a known linear dynamical system for which partial state information, such as …

Abstract Model predictive control allows to provide high performance and safety guarantees
in the form of constraint satisfaction. These properties, however, can be satisfied only if the …