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Sebastian Huch
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Tum autonomous motorsport: An autonomous racing software for the indy autonomous challenge
J Betz, T Betz, F Fent, M Geisslinger, A Heilmeier, L Hermansdorfer, ...
Journal of Field Robotics 40 (4), 783-809, 2023
532023
Indy autonomous challenge-autonomous race cars at the handling limits
A Wischnewski, M Geisslinger, J Betz, T Betz, F Fent, A Heilmeier, ...
12th International Munich Chassis Symposium 2021: chassis. tech plus, 163-182, 2022
502022
Benchmarking and functional decomposition of automotive lidar sensor models
P Rosenberger, M Holder, S Huch, H Winner, T Fleck, MR Zofka, ...
2019 IEEE Intelligent Vehicles Symposium (IV), 632-639, 2019
332019
Multi-modal sensor fusion and object tracking for autonomous racing
P Karle, F Fent, S Huch, F Sauerbeck, M Lienkamp
IEEE Transactions on Intelligent Vehicles 8 (7), 3871-3883, 2023
162023
Quantifying the lidar sim-to-real domain shift: A detailed investigation using object detectors and analyzing point clouds at target-level
S Huch, L Scalerandi, E Rivera, M Lienkamp
IEEE Transactions on Intelligent Vehicles 8 (4), 2970-2982, 2023
152023
EDGAR: An Autonomous Driving Research Platform--From Feature Development to Real-World Application
P Karle, T Betz, M Bosk, F Fent, N Gehrke, M Geisslinger, L Gressenbuch, ...
arXiv preprint arXiv:2309.15492, 2023
132023
Multi-task end-to-end self-driving architecture for CAV platoons
S Huch, A Ongel, J Betz, M Lienkamp
Sensors 21 (4), 1039, 2021
132021
Learn to see fast: Lessons learned from autonomous racing on how to develop perception systems
F Sauerbeck, S Huch, F Fent, P Karle, D Kulmer, J Betz
IEEE Access 11, 44034-44050, 2023
52023
DeepSTEP-Deep Learning-Based Spatio-Temporal End-To-End Perception for Autonomous Vehicles
S Huch, F Sauerbeck, J Betz
2023 IEEE Intelligent Vehicles Symposium (IV), 1-8, 2023
32023
Towards Minimizing the LiDAR Sim-to-Real Domain Shift: Object-Level Local Domain Adaptation for 3D Point Clouds of Autonomous Vehicles
S Huch, M Lienkamp
Sensors 23 (24), 9913, 2023
22023
Entwicklung einer umfassenden Metrik für die Bewertung einer Lidar-Sensor-Simulation durch Betrachtung mehrerer aufeinander folgender Verarbeitungsebenen
S Huch
Technische Universität Darmstadt, 2018
22018
S2R-DAD: Sim-to-Real Distribution-Aligned Dataset
S Huch, L Scalerandi, E Rivera, M Lienkamp
https://doi.org/10.14459/2023mp1695833, 2023
2023
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