75 citations · 132 across the 5 of their papers we have counts for
6 papers
TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge
Johannes Betz, Tobias Betz, Felix Fent +16
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…
Indy Autonomous Challenge -- Autonomous Race Cars at the Handling Limits
Alexander Wischnewski, Maximilian Geisslinger, Johannes Betz +15
Motorsport has always been an enabler for technological advancement, and the same applies to the autonomous driving industry. The team TUM Auton-omous Motorsports will participate…
Radar Voxel Fusion for 3D Object Detection
Felix Nobis, Ehsan Shafiei, Phillip Karle +2
Automotive traffic scenes are complex due to the variety of possible scenarios, objects, and weather conditions that need to be handled. In contrast to more constrained environment…
A Deep Learning-based Radar and Camera Sensor Fusion Architecture for Object Detection
Felix Nobis, Maximilian Geisslinger, Markus Weber +2
Object detection in camera images, using deep learning has been proven successfully in recent years. Rising detection rates and computationally efficient network structures are pus…
Persistent Map Saving for Visual Localization for Autonomous Vehicles: An ORB-SLAM Extension
Felix Nobis, Odysseas Papanikolaou, Johannes Betz +1
Electric vhicles and autonomous driving dominate current research efforts in the automotive sector. The two topics go hand in hand in terms of enabling safer and more environmental…
Exploring the Capabilities and Limits of 3D Monocular Object Detection -- A Study on Simulation and Real World Data
Felix Nobis, Fabian Brunhuber, Simon Janssen +2
3D object detection based on monocular camera data is a key enabler for autonomous driving. The task however, is ill-posed due to lack of depth information in 2D images. Recent dee…