49 citations · 272 across the 27 of their papers we have counts for
35 papers
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…
User Feedback and Sample Weighting for Ill-Conditioned Hand-Eye Calibration
Markus Horn, Thomas Wodtko, Michael Buchholz +1
Hand-eye calibration is an important and extensively researched method for calibrating rigidly coupled sensors, solely based on estimates of their motion. Due to the geometric stru…
Adaptive Patched Grid Mapping
Thomas Wodtko, Thomas Griebel, Michael Buchholz
In this work, we propose a novel adaptive grid mapping approach, the Adaptive Patched Grid Map, which enables a situational aware grid based perception for autonomous vehicles. Its…
Advancing Frame-Dropping in Multi-Object Tracking-by-Detection Systems Through Event-Based Detection Triggering
Matti Henning, Michael Buchholz, Klaus Dietmayer
With rising computational requirements modern automated vehicles (AVs) often consider trade-offs between energy consumption and perception performance, potentially jeopardizing the…
Automated Automotive Radar Calibration With Intelligent Vehicles
Alexander Tsaregorodtsev, Michael Buchholz, Vasileios Belagiannis
While automotive radar sensors are widely adopted and have been used for automatic cruise control and collision avoidance tasks, their application outside of vehicles is still limi…
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…
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…
RT-K-Net: Revisiting K-Net for Real-Time Panoptic Segmentation
Markus Schön, Michael Buchholz, Klaus Dietmayer
Panoptic segmentation is one of the most challenging scene parsing tasks, combining the tasks of semantic segmentation and instance segmentation. While much progress has been made,…
Automated Static Camera Calibration with Intelligent Vehicles
Alexander Tsaregorodtsev, Adrian Holzbock, Jan Strohbeck +2
Connected and cooperative driving requires precise calibration of the roadside infrastructure for having a reliable perception system. To solve this requirement in an automated man…
Integration of Reinforcement Learning Based Behavior Planning With Sampling Based Motion Planning for Automated Driving
Marvin Klimke, Benjamin Völz, Michael Buchholz
Reinforcement learning has received high research interest for developing planning approaches in automated driving. Most prior works consider the end-to-end planning task that yiel…
The Impact of Frame-Dropping on Performance and Energy Consumption for Multi-Object Tracking
Matti Henning, Michael Buchholz, Klaus Dietmayer
The safety of automated vehicles (AVs) relies on the representation of their environment. Consequently, state-of-the-art AVs employ potent sensor systems to achieve the best possib…
Automatic Intersection Management in Mixed Traffic Using Reinforcement Learning and Graph Neural Networks
Marvin Klimke, Benjamin Völz, Michael Buchholz
Connected automated driving has the potential to significantly improve urban traffic efficiency, e.g., by alleviating issues due to occlusion. Cooperative behavior planning can be…
Extrinsic Camera Calibration with Semantic Segmentation
Alexander Tsaregorodtsev, Johannes Müller, Jan Strohbeck +3
Monocular camera sensors are vital to intelligent vehicle operation and automated driving assistance and are also heavily employed in traffic control infrastructure. Calibrating th…
Situation-Aware Environment Perception for Decentralized Automation Architectures
Matti Henning, Michael Buchholz, Klaus Dietmayer
Advances in the field of environment perception for automated agents have resulted in an ongoing increase in generated sensor data. The available computational resources to process…
An Enhanced Graph Representation for Machine Learning Based Automatic Intersection Management
Marvin Klimke, Jasper Gerigk, Benjamin Völz +1
The improvement of traffic efficiency at urban intersections receives strong research interest in the field of automated intersection management. So far, mostly non-learning algori…
Identification of Threat Regions From a Dynamic Occupancy Grid Map for Situation-Aware Environment Perception
Matti Henning, Jan Strohbeck, Michael Buchholz +1
The advance towards higher levels of automation within the field of automated driving is accompanied by increasing requirements for the operational safety of vehicles. Induced by t…
MGNet: Monocular Geometric Scene Understanding for Autonomous Driving
Markus Schön, Michael Buchholz, Klaus Dietmayer
We introduce MGNet, a multi-task framework for monocular geometric scene understanding. We define monocular geometric scene understanding as the combination of two known tasks: Pan…
Self-Assessment for Single-Object Tracking in Clutter Using Subjective Logic
Thomas Griebel, Johannes Müller, Paul Geisler +4
Reliable tracking algorithms are essential for automated driving. However, the existing consistency measures are not sufficient to meet the increasing safety demands in the automot…
Cooperative Behavior Planning for Automated Driving using Graph Neural Networks
Marvin Klimke, Benjamin Völz, Michael Buchholz
Urban intersections are prone to delays and inefficiencies due to static precedence rules and occlusions limiting the view on prioritized traffic. Existing approaches to improve tr…
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…
Situation-Aware Environment Perception Using a Multi-Layer Attention Map
Matti Henning, Johannes Müller, Fabian Gies +2
Within the field of automated driving, a clear trend in environment perception tends towards more sensors, higher redundancy, and overall increase in computational power. This is m…
Motion Planning for Connected Automated Vehicles at Occluded Intersections With Infrastructure Sensors
Johannes Müller, Jan Strohbeck, Martin Herrmann +1
Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on th…
Anomaly Detection in Radar Data Using PointNets
Thomas Griebel, Dominik Authaler, Markus Horn +3
For autonomous driving, radar is an important sensor type. On the one hand, radar offers a direct measurement of the radial velocity of targets in the environment. On the other han…
Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions
Markus Horn, Thomas Wodtko, Michael Buchholz +1
In this work, we propose an approach for extrinsic sensor calibration from per-sensor ego-motion estimates. Our problem formulation is based on dual quaternions, enabling two diffe…