activity
20202026
most cited3D Point Cloud Compression with Recurrent Neural Network and Image Compression Methods

10 citations · 14 across the 13 of their papers we have counts for

collaborators

13 papers

cs.RO2026

A Five-Layer MLOps Architecture for Connected Automated Driving

Bastian Lampe, Lutz Eckstein

The continual assurance of safety and performance of automated driving systems (ADSs) poses significant challenges. ADSs operate in complex, dynamic, open-world environments allowi…

cs.AR2026

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…

cs.RO2025

Application Management in C-ITS: Orchestrating Demand-Driven Deployments and Reconfigurations

Lukas Zanger, Bastian Lampe, Lennart Reiher +1

Vehicles are becoming increasingly automated and interconnected, enabling the formation of cooperative intelligent transport systems (C-ITS) and the use of offboard services. As a…

cs.RO2024

CARLOS: An Open, Modular, and Scalable Simulation Framework for the Development and Testing of Software for C-ITS

Christian Geller, Benedikt Haas, Amarin Kloeker +4

Future mobility systems and their components are increasingly defined by their software. The complexity of these cooperative intelligent transport systems (C-ITS) and the everchang…

cs.CV2024★ 10 cited

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…

cs.CV2024

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…

cs.RO2023★ 1 cited

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…

cs.RO2023★ 1 cited

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…

cs.RO2022

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…

cs.RO2022★ 1 cited

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…

cs.RO2021

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…

cs.CV2020★ 1 cited

A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird's Eye View

Lennart Reiher, Bastian Lampe, Lutz Eckstein

Accurate environment perception is essential for automated driving. When using monocular cameras, the distance estimation of elements in the environment poses a major challenge. Di…

eess.SP2020

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…