Recent Publications

More Publications

. FeatSense -- A Feature-based Registration Algorithm with GPU-accelerated TSDF-Mapping Backend for NVIDIA Jetson Boards. IRC 2023, 2023.

Preprint PDF Code

. Towards 6D MCL for LiDARs in 3D TSDF Maps on Embedded Systems with GPUs. IRC 2023, 2023.

Preprint PDF Code

. Rmagine: 3D Range Sensor Simulation in Polygonal Maps via Ray Tracing for Embedded Hardware on Mobile Robots. ICRA 2023, 2023.

PDF Code Video

. ReDroSe — Reconfigurable Drone Setup for Resource-efficient SLAM. DroneSE-2023, 2023.

PDF

. Computing Arbitrarily Large Meshes with Level-of-Detail Support for Cesium 3D Tiles. LowCost3D 2023, 2022.

PDF

Projects

All Localization Planning Mapping Navigation Semantics

3DinOS

In quite a few projects world-wide, 3D Mapping technology has been used for documenting historical buildings – typically involving a massive amount of time and person power for both the data capture and their processing for public access (if that is granted at all). This can be afforded for eminent buildings like the Pantheon in Rome or the Cologne Cathedral; it is prohibitive for the many thousands of listed historic buildings constituting the cultural heritage of a whole region. 3DInOs was a study for developing and exemplifying a concept how to document historical buildings in a level of detail satisfying art historians’ needs and involving much limited cost for capturing, processing, and archiving the data, owing to the automatization and standardization of many of the processes and data formats involved.

LiSA

The LiSA project was funded by BMBF (Bundesministerium für Bildung und Forschung). Project duration was 1.4.2006 - 31.7.2009. The goal was to develop an autonomous mobile robot as a system assisting in a life-science research lab environment.

MACS

MACS – Multi-sensory Autonomous Cognitive Systems. The MACS project is a Specifically Targeted Research Project (STReP) for Exploring and Exploiting the Concept of Affordances for Robot Control. The project is funded by the European Commission’s 6th Framework Programme IST under contract/grant number FP6-004381. The Commission’s support is gratefully acknowledged.

Move Base Flex

Move Base Flex (MBF) is a backwards-compatible replacement for move_base. MBF can use existing plugins for move_base, and provides an enhanced version of the planner, controller and recovery plugin ROS interfaces. It exposes action servers for planning, controlling and recovering, providing detailed information of the current state and the plugin’s feedback. An external executive logic can use MBF and its actions to perform smart and flexible navigation strategies. Furthermore, MBF enables the use of other map representations, e.g. meshes or grid_map This package is a meta package and refers to the Move Base Flex stack packages.The abstract core of MBF – without any binding to a map representation – is represented by the mbf_abstract_nav and the mbf_abstract_core. For navigation on costmaps see mbf_costmap_nav and mbf_costmap_core.

RACE

Robustness by Autonomous Competence Enhancement

SOILAssist - Nachhaltige Sicherung und Verbesserung von Boden-funktionen durch intelligente Landbewirtschaftung – Ein Echtzeit-Assistenzsystem für die Praxis

Das interdisziplinäre Forschungsprojekt SOILAssist befasst sich mit dem landwirtschaftlichen Bodenschutz bei der Befahrung von Ackerflächen und verfolgt das Ziel, negative Veränderungen der Bodenstruktur und -funktionalität frühzeitig zu erkennen und zu vermeiden. Durch angepasstes Management soll ein günstiger Bodenzustand erhalten und verbessert werden. Im Rahmen des Teilprojektes ‘Adaptives Semantisches Planungssystem’ arbeiten die Projektpartner DFKI und UOS gemeinsam an einem adaptiven semantischen Assistenzsystem für den Feldeinsatz mit mehreren kooperativen Maschinen sowie der Integration einer geometrischen Umgebungsdarstellung.

Tags

3D Mapping 3D laser scanning 3D scanner 3D sensing 6D localization Action Selection Affordances Agriculture BVH CG CHIMP CUDA Camera Tracking Closed-loop mapping Crop/weed discrimination DGM Digitaler Zwilling Dimensionality reduction Draco Embree Environment modeling Extended paper FPGA Feldroboter Gazebo Gibson HDF5 HTN planner HTN planning Hyperspectal Incremental mapping Jetson Kinect Fusion LVR LVR2 LiDAR MPI Mapping Markov Mesh Generation Mesh Optimization Model-based object recognition Monte-Carlo Planning Ontologies OpenGL OptiX Optimization Partial observability Path Planning Plan-based Robot Control Planning Under Uncertainty Planning under Uncertainty Plant classification Point Clouds Polygonal mapping Problem Solving RMCL ROS RTX Rmagine Robot Navigation SEM SLAM Segmentation Semantic map Semantic mapping Simulation Spectral imaging Surface Reconstruction Surface reconstruction TSDF VR affordance-based planning affordances answer set autonomous mobile robots autonomous robots behavior-based robot control classification cognitive robotics computational geometry controll data analysis data structures deep learning ecological psychology event generation flexible navigation function-centered perception geographic information systems hdf5 heuristic searches hierarchical task networks hybrid robot control architectures hyperspectral hyperspectral data image features image registration knowledge acquisition knowledge base labelling loop closure lvr machine-learning mapping maps mesh generation mesh localization mesh navigation mesh reconstruction mesh tools mobile robot mobile robots move base move base flex navigation neuronal gas normal estimation object detection obstacle detection path planning point clouds probabilistic localization probabilistic robotics rasberry pi ray tracing robot dynamics robot localization robot planning roboter control robotics ros scanning segmentation semantic environment modelling semantic mapping semantic maps sensor data interpretation service robots simulation social intelligence stream processing surface reconstruction tesselation textures triangle meshes visual databases waveform