activity
20202024
most citedThe Radar Ghost Dataset -- An Evaluation of Ghost Objects in Automotive Radar Data

35 citations · 74 across the 12 of their papers we have counts for

collaborators

13 papers

cs.RO2024★ 3 cited

Self-Assessment of Evidential Grid Map Fusion for Robust Motion Planning

Oliver Schumann, Thomas Wodtko, Michael Buchholz +1

Conflicting sensor measurements pose a huge problem for the environment representation of an autonomous robot. Therefore, in this paper, we address the self-assessment of an eviden…

cs.CV2024★ 35 cited

The Radar Ghost Dataset -- An Evaluation of Ghost Objects in Automotive Radar Data

Florian Kraus, Nicolas Scheiner, Werner Ritter +1

Radar sensors have a long tradition in advanced driver assistance systems (ADAS) and also play a major role in current concepts for autonomous vehicles. Their importance is reasone…

cs.RO2023★ 5 cited

Efficient Path Planning in Large Unknown Environments with Switchable System Models for Automated Vehicles

Oliver Schumann, Michael Buchholz, Klaus Dietmayer

Large environments are challenging for path planning algorithms as the size of the configuration space increases. Furthermore, if the environment is mainly unexplored, large amount…

cs.RO2023★ 12 cited

Real-Time Spatial Trajectory Planning for Urban Environments Using Dynamic Optimization

Jona Ruof, Max Bastian Mertens, Michael Buchholz +1

Planning trajectories for automated vehicles in urban environments requires methods with high generality, long planning horizons, and fast update rates. Using a path-velocity decom…

cs.RO2023★ 7 cited

Extrinsic Infrastructure Calibration Using the Hand-Eye Robot-World Formulation

Markus Horn, Thomas Wodtko, Michael Buchholz +1

We propose a certifiably globally optimal approach for solving the hand-eye robot-world problem supporting multiple sensors and targets at once. Further, we leverage this formulati…

cs.CV2023

LMR: Lane Distance-Based Metric for Trajectory Prediction

Julian Schmidt, Thomas Monninger, Julian Jordan +1

The development of approaches for trajectory prediction requires metrics to validate and compare their performance. Currently established metrics are based on Euclidean distance, w…

cs.CV2023

Tackling Clutter in Radar Data -- Label Generation and Detection Using PointNet++

Johannes Kopp, Dominik Kellner, Aldi Piroli +1

Radar sensors employed for environment perception, e.g. in autonomous vehicles, output a lot of unwanted clutter. These points, for which no corresponding real objects exist, are a…

cs.CV2023★ 2 cited

Gesture Recognition with Keypoint and Radar Stream Fusion for Automated Vehicles

Adrian Holzbock, Nicolai Kern, Christian Waldschmidt +2

We present a joint camera and radar approach to enable autonomous vehicles to understand and react to human gestures in everyday traffic. Initially, we process the radar data with…

cs.CV2022

Transformers for Object Detection in Large Point Clouds

Felicia Ruppel, Florian Faion, Claudius Gläser +1

We present TransLPC, a novel detection model for large point clouds that is based on a transformer architecture. While object detection with transformers has been an active field o…

cs.RO2022★ 10 cited

Globally Optimal Multi-Scale Monocular Hand-Eye Calibration Using Dual Quaternions

Thomas Wodtko, Markus Horn, Michael Buchholz +1

In this work, we present an approach for monocular hand-eye calibration from per-sensor ego-motion based on dual quaternions. Due to non-metrically scaled translations of monocular…

cs.RO2021

Graph-based Motion Planning for Automated Vehicles using Multi-model Branching and Admissible Heuristics

Oliver Speidel, Jona Ruof, Klaus Dietmayer

Automated driving in urban scenarios requires efficient planning algorithms able to handle complex situations in real-time. A popular approach is to use graph-based planning method…

cs.RO2020

On-Road Motion Planning for Automated Vehicles at Ulm University

Maximilian Graf, Oliver Speidel, Jona Ruof +1

The Institute of Measurement, Control and Microtechnology at Ulm University investigates advanced driver assistance systems for decades and concentrates in large parts on autonomou…

cs.RO2020

Trajectory Planning for Automated Driving in Intersection Scenarios using Driver Models

Oliver Speidel, Maximilian Graf, Ankit Kaushik +3

Efficient trajectory planning for urban intersections is currently one of the most challenging tasks for an Autonomous Vehicle (AV). Courteous behavior towards other traffic partic…