Intelligent vehicles (IVs) have gained worldwide attention due to their increased
convenience, safety advantages, and potential commercial value. Despite predictions of …

In this review, we provide an overview of emerging trends and challenges in the field of
intelligent and autonomous, or self-driving, vehicles. Recent advances in the field of …

We present a simple yet effective approach that can transform the OpenAI GPT-3.5 model
into a reliable motion planner for autonomous vehicles. Motion planning is a core challenge …

The rising popularity of self-driving cars has led to the emergence of a new research field in
recent years: Autonomous racing. Researchers are developing software and hardware for …

The optimal performance of robotic systems is usually achieved near the limit of state and
input bounds. Model predictive control (MPC) is a prevalent strategy to handle these …

In many robotic tasks, such as autonomous drone racing, the goal is to travel through a set of
waypoints as fast as possible. A key challenge for this task is planning the timeoptimal …

In this letter, we present a learning-based control approach for autonomous racing with an
application to the AMZ Driverless race car gotthard. One major issue in autonomous racing …

This paper presents the acados software package, a collection of solvers for fast embedded
optimization intended for fast embedded applications. Its interfaces to higher-level …

We present foundations for using Model Predictive Control (MPC) as a differentiable policy
class for reinforcement learning. This provides one way of leveraging and combining the …

In this article, we tackle the problem of flying time-optimal trajectories through multiple
waypoints with quadrotors. State-of-the-art solutions split the problem into a planning task …