35 citations · 74 across the 12 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
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…
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…
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…
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…