In this work, an adaptive learning model predictive control (ALMPC) scheme is proposed for
the trajectory tracking of perturbed autonomous ground vehicles (AGVs) subject to input …

… (MPC) and its wide applications to both single and multiple autonomous ground vehicles
(… In [80], a learning MPC-based motion controller for a racing car is proposed, which …

… Reinforcement learning can in principle forego the need for explicit state estimation and …
combine MPC with reinforcement learning in the framework of guided policy search, where MPC …

… works and learn to solve tasks defined by simple and easily interpretable high level objectives
on a real unmanned ground vehicle (UGV). This is reputably challenging for most MPC …

This paper focuses on the trajectory tracking control problem for an articulated unmanned
ground vehicle. We propose and compare two approaches in terms of performance and …

… Compared to a dual antenna setup, a single antenna system has to learn the vehicle orienta…
presented two MPC approaches for trajectory following for autonomous ground vehicles with …

… and makes real vehicle applications difficult. In addition, there are learning-based MPCs [44…
driving on a flat road firstly, examining the accuracy of the vehicle model in the MPC and the …

… simulators, albeit using a ground truth model. The fusion of … vehicle in [11] consisted of
100 parameters and a single matrix multiply, whereas the neural network model that we learn …

… utilize adaptive nonlinear MPC for tracking control of vehicle. Elbanhawi et al. propose a
model predictive active yaw control implementation for pure pursuit path tracking. …

… MPC for motion control of both unmanned ground vehicles (UGVs) and unmanned aerial
vehicles (… mainly on combining MPC with learning techniques. These new approaches such as …