activity
20192023
most citedMGNet: Monocular Geometric Scene Understanding for Autonomous Driving

49 citations · 272 across the 27 of their papers we have counts for

collaborators
Showing 2023Show all

12 papers · 1 filter

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

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…

cs.RO2023

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…

cs.RO2023

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…

cs.RO2023

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…

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…