1 citations · 1 across the 7 of their papers we have counts for
7 papers
Stability Control for Real World Testing in Autonomous Racing
Phillip Pitschi, Simon Sagmeister, Frederik Werner +2
Controlling an autonomous vehicle at the limits of handling is a challenging task. Due to external influences, such as road conditions or weather, a vehicle can easily become unsta…
Beyond the Plane: Coupling Planar Vehicle Dynamics with Three-Dimensional Road Geometry
Simon Sagmeister, Phillip Pitschi, Nico Haja +1
Simulation is crucial for developing and testing autonomous driving systems. In particular, the development of localization and control algorithms relies on an accurate vehicle dyn…
Benchmarking Empirical and Learning-Based Approaches for Feedforward Steering Control in Autonomous Racing
Georg Jank, Mattia Piccinini, Sebastian Wenk +3
Feedforward steering control is a key component of hierarchical control architectures for autonomous racing. The goal is to reduce steering corrections from the feedback controller…
Head-to-Head autonomous racing at the limits of handling in the A2RL challenge
Simon Hoffmann, Simon Sagmeister, Tobias Betz +17
Autonomous racing presents a complex challenge involving multi-agent interactions between vehicles operating at the limit of performance and dynamics. As such, it provides a valuab…
RSLCPP -- Deterministic Simulations Using ROS 2
Simon Sagmeister, Marcel Weinmann, Phillip Pitschi +1
Simulation is crucial in real-world robotics, offering safe, scalable, and efficient environments for developing a variety of robotic applications. While the Robot Operating System…
Longitudinal Control for Autonomous Racing with Combustion Engine Vehicles
Phillip Pitschi, Simon Sagmeister, Sven Goblirsch +2
Usually, a controller for path- or trajectory tracking is employed in autonomous driving. Typically, these controllers generate high-level commands like longitudinal acceleration o…
Trajectory Planning Using Reinforcement Learning for Interactive Overtaking Maneuvers in Autonomous Racing Scenarios
Levent Ögretmen, Mo Chen, Phillip Pitschi +1
Conventional trajectory planning approaches for autonomous racing are based on the sequential execution of prediction of the opposing vehicles and subsequent trajectory planning fo…