Develo** autonomous driving technologies necessitates addressing safety and cost
concerns. Both academic research and commercial applications of autonomous driving …

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

Policy search and model predictive control (MPC) are two different paradigms for robot
control: policy search has the strength of automatically learning complex policies using …

For decades, motorsport has been an incubator for innovations in the automotive sector and
brought forth systems, like, disk brakes or rearview mirrors. Autonomous racing series such …

Automatic overtaking is a challenging task for self-driving vehicles. Traditional rule-based
methods for overtaking in autonomous driving heavily rely on many predefined rules and are …

This paper presents a multi-layer motion planning and control architecture for autonomous
racing, capable of avoiding static obstacles, performing active overtakes, and reaching …

Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …

Urban autonomous driving is a difficult task because of its complex road scenarios and the
interaction between multiple vehicles. Autonomous vehicles need to balance multiple …

Scene transfer for vision-based mobile robotics applications is a highly relevant and
challenging problem. The utility of a robot greatly depends on its ability to perform a task in …

This paper presents a novel planning and control strategy for competing with multiple
vehicles in a car racing scenario. The proposed racing strategy switches between two …