10 citations · 13 across the 10 of their papers we have counts for
10 papers
Query2Uncertainty: Robust Uncertainty Quantification and Calibration for 3D Object Detection under Distribution Shift
Till Beemelmanns, Alexey Nekrasov, Stefan Vilceanu +4
Reliable uncertainty estimation for 3D object detection is critical for deploying safe autonomous systems, yet modern detectors remain poorly calibrated, especially under distribut…
karl. -- A Research Vehicle for Automated and Connected Driving
Jean-Pierre Busch, Lukas Ostendorf, Guido Linden +5
As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in selected areas (e.g., Waymo), automated d…
3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods
Till Beemelmanns, Yuchen Tao, Bastian Lampe +4
Storing and transmitting LiDAR point cloud data is essential for many AV applications, such as training data collection, remote control, cloud services or SLAM. However, due to the…
Enhancing Lidar-based Object Detection in Adverse Weather using Offset Sequences in Time
Raphael van Kempen, Tim Rehbronn, Abin Jose +4
Automated vehicles require an accurate perception of their surroundings for safe and efficient driving. Lidar-based object detection is a widely used method for environment percept…
RobotKube: Orchestrating Large-Scale Cooperative Multi-Robot Systems with Kubernetes and ROS
Bastian Lampe, Lennart Reiher, Lukas Zanger +3
Modern cyber-physical systems (CPS) such as Cooperative Intelligent Transport Systems (C-ITS) are increasingly defined by the software which operates these systems. In practice, mi…
Combined Registration and Fusion of Evidential Occupancy Grid Maps for Live Digital Twins of Traffic
Raphael van Kempen, Laurenz Adrian Heidrich, Bastian Lampe +2
Cooperation of automated vehicles (AVs) can improve safety, efficiency and comfort in traffic. Digital twins of Cooperative Intelligent Transport Systems (C-ITS) play an important…
Data-Driven Occupancy Grid Mapping using Synthetic and Real-World Data
Raphael van Kempen, Bastian Lampe, Lennart Reiher +3
In perception tasks of automated vehicles (AVs) data-driven have often outperformed conventional approaches. This motivated us to develop a data-driven methodology to compute occup…
Enabling Connectivity for Automated Mobility: A Novel MQTT-based Interface Evaluated in a 5G Case Study on Edge-Cloud Lidar Object Detection
Lennart Reiher, Bastian Lampe, Timo Woopen +3
Enabling secure and reliable high-bandwidth lowlatency connectivity between automated vehicles and external servers, intelligent infrastructure, and other road users is a central s…
A Simulation-based End-to-End Learning Framework for Evidential Occupancy Grid Mapping
Raphael van Kempen, Bastian Lampe, Timo Woopen +1
Evidential occupancy grid maps (OGMs) are a popular representation of the environment of automated vehicles. Inverse sensor models (ISMs) are used to compute OGMs from sensor data…
Reducing Uncertainty by Fusing Dynamic Occupancy Grid Maps in a Cloud-based Collective Environment Model
Bastian Lampe, Raphael van Kempen, Timo Woopen +3
Accurate environment perception is essential for automated vehicles. Since occlusions and inaccuracies regularly occur, the exchange and combination of perception data of multiple…