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RadaRays: Real-Time Simulation of Rotating FMCW Radar for Mobile robotics via Hardware-Accelerated Ray Tracing

IEEE robotICS AND AUTOMATION LETTERS 2025年第3期10卷 2470-2477页

作者： Mock, Alexander Magnusson, Martin Hertzberg, Joachim Osnabruck Univ KBS Grp D-49074 Osnabruck Germany Orebro Univ RNP Lab AASS Res Ctr S-70182 Orebro Sweden DFKI Niedersachsen Plan based Robot Control Grp D-49084 Osnabruck Germany

RadaRays allows for the accurate modeling and simulation of rotating FMCW radar sensors in complex environments, including the simulation of reflection, refraction, and scattering of radar waves. Our software is able to handle large numbers of objects and materials in real-time, making it suitable for use in a variety of mobile robotics applications. We demonstrate the effectiveness of RadaRays through a series of experiments and show that it can more accurately reproduce the behavior of FMCW radar sensors in a variety of environments, compared to the ray casting-based lidar-like simulations that are commonly used in simulators for autonomous driving such as CARLA. Our experiments additionally serve as a valuable reference point for researchers to evaluate their own radar simulations. By using RadaRays, developers can significantly reduce the time and cost associated with prototyping and testing FMCW radar-based algorithms. We also provide a Gazebo plugin that makes our work accessible to the mobile robotics community.

关键词： Radar Radar imaging robots Spaceborne radar Ray tracing Meteorological radar Real-time systems Radar scattering Radar antennas Radar cross-sections Simulation and animation range sensing software tools for robot programming SLAM collision avoidance

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Comparative analysis of UAV-based LiDAR and photogrammetric systems for the detection of terrain anomalies in a historical conflict landscape

SCIENCE OF REMOTE SENSING

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SCIENCE OF REMOTE SENSING 2025年 11卷

作者： Storch, Marcel Kisliuk, Benjamin Jarmer, Thomas Waske, Bjoern de Lange, Norbert Osnabruck Univ Inst Comp Sci Remote Sensing & Digital Image Anal Wachsble 27 D-49090 Osnabruck Germany Osnabruck Univ Inst Comp Sci Environ Informat & Municipal Plannin Wachsble 27 D-49090 Osnabruck Germany German Res Ctr Artificial Intelligence Plan Based Robot Control Grp Hamburger Str 24 D-49084 Osnabruck Germany

The documentation of historical artefacts and cultural heritage using high-resolution data obtained from unmanned aerial vehicles (UAVs) is of paramount importance in the preservation of historical knowledge. This study compares three UAV-based systems for the detection of historically relevant terrain anomalies in a conflict landscape. Two laser scanners, a high-end (RIEGL miniVUX-1UAV) and a lower priced model (DJI Zenmuse L1), along with a cost-effective optical camera system (photogrammetry using Structure from Motion, SfM) were employed in two study sites with different densities of vegetation. In the study area with deciduous trees and little low vegetation, the DJI Zenmuse L1 system performs comparably to the RIEGL miniVUX-1UAV, with higher completeness but lower correctness. The SfM method demonstrated inferior performance with respect to correctness and the F1-score, yet achieved comparable or higher completeness values compared to the laser scanners (maximum 1.0, median 0.84). In the study area characterized by dense near-ground vegetation, the detection results are less optimal. However, the RIEGL miniVUX-1UAV system still demonstrates superior results in anomaly detection (F1-score maximum 0.61, median 0.53) compared to the other systems. The DJI Zenmuse L1 data showed lower performance (F1-score maximum 0.56, median 0.46). Both laser scanners exhibited enhanced results in comparison to the SfM approach, with a maximum F1-score of 0.12. Hence, the SfM method is viable under specific conditions, such as defoliated trees without dense low vegetation. Therefore, lower-cost systems can offer cost-effective alternatives to the high-end LiDAR system in suitable environments. However, limitations persist in densely vegetated areas.

关键词： Historical terrain anomalies UAV-based remote sensing LiDAR vs. photogrammetry Vegetation impact

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Online Knowledge Integration for 3d Semantic Mapping: A Survey

SSRN

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SSRN 2025年

作者： Igelbrink, Felix Renz, Marian Günther, Martin Powell, Piper Niecksch, Lennart Lima, Oscar Atzmueller, Martin Hertzberg, Joachim German Research Center for Artificial Intelligence Research Department Plan-based Robot Control Osnabrück Germany Osnabrück University Institute of Computer Science Knowledge-Based Systems Group Osnabrück Germany Osnabrück University Institute of Computer Science Semantic Information Systems Group Osnabrück Germany

Semantic mapping is a key component of robots operating in and interacting with objects in structured environments. Traditionally, geometric and knowledge representations within a semantic map have only been loosely integrated. However, recent advances in deep learning now allow full integration of prior knowledge, represented as knowledge graphs or language concepts, into sensor data processing and semantic mapping pipelines. Semantic scene graphs and language models enable modern semantic mapping approaches to incorporate graph-based prior knowledge or to leverage the rich information in human language both during and after the mapping process. This has sparked substantial advances in semantic mapping, leading to previously impossible novel applications. This survey reviews these recent developments comprehensively, with a focus on online integration of knowledge into semantic mapping. We specifically focus on methods using semantic scene graphs for integrating symbolic prior knowledge and language models for respective capture of implicit common-sense knowledge and natural language concepts. © 2025, The Authors. All rights reserved.

关键词： Knowledge graph

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AI in Current and Future Agriculture: An Introductory Overview

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KUNSTLICHE INTELLIGENZ 2023年第2-4期37卷 117-132页

作者： Kisliuk, Benjamin Krause, Jan Christoph Meemken, Hendrik Saborio Morales, Juan Carlos Mueller, Henning Hertzberg, Joachim DFKI Plan Based Robot Control Grp Osnabruck Germany Osnabruck Univ Inst Comp Sci Osnabruck Germany

In recent years, agriculture has become a major field of application and transfer for AI. The paper gives an overview of the topic, focusing agricultural processes and technology in Central-European style arable farming. AI could also be part of the transformation process of agriculture that is emerging world-wide in response to the UN global sustainable development goals (SDGs). In that sense, our overview includes pointers to some research towards AI in future agricultural systems.

关键词： Agricultural technology Smart farming Agricultural robotics

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Automated Byproduct Segmentation In Grain Images 14

Automated Byproduct Segmentation In Grain Images

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14th International Conference on Machine Vision (ICMV)

作者： Herrmann, Lena Brust, Johannes Hertzberg, Joachim Osnabruck Univ Knowledge Based Syst Grp Osnabruck Germany DFKI Lab Niedersachsen Plan Based Robot Control Osnabruck Germany

ISBN: (数字)9781510650459

ISBN: (纸本)9781510650459;9781510650442

Within the farming industry using computer vision technologies provides great support for various processes. One example is the grain harvest with a combine harvester, which requires excellent expert knowledge to reach a certain level of quality. This means the amount of byproducts including straw and hulls should be as small as possible. Inside a combine harvester several sensors are installed which deliver important information about the current harvesting state. This includes a visual based sensor that constantly delivers images to the driver about the composition of the processed grain. Normally, it is the driver's task to decide if the quality is sufficient or if machine settings need to be adjusted to improve the outcome. Yet, resolving this task entirely manually is rather error prone, due to the high amount of fairly similar images that need to be analyzed in a short time. Therefore we designed and implemented a system that is able to automatically detect unwanted byproducts within the wheat harvest and highlight those parts inside images delivered by the visual sensor. The system itself is a combination of an automated preprocessing step and a variation of a U-Net. The preprocessing step filters unwanted byproducts and is able to automatically generate training data for the U-Net. The U-Net is lightweight, easy to train and can potentially be used onboard the combine harvester.

关键词： machine vision farming combine harvester image segmentation neural networks automated preprocessing

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A systematic approach to the development of long-term autonomous robotic systems for agriculture 43

A systematic approach to the development of long-term autono...

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43. Jahrestagung der Gesellschaft fur Informatik in der Land-, Forst- und Ernahrungswirtschaft - Resiliente Agri-Food-Systeme: Herausforderungen und Losungsansatze, GIL 2023 - 43rd Annual Conference of the Society for Informatics in Agriculture, Forestry, and Food Industry - Resilient Agri-Food Systems: Challenges and Solutions, GIL 2023

作者： Bohne, Tim Parthasarathy, Gurunatraj Kisliuk, Benjamin GmbH Plan-Based Robot Control Berghoffstraße 11 Osnabrueck49090 Germany

ISBN: (纸本)9783885797241

For robots to compete with conventional machinery in agriculture, improving their long-term autonomy seems necessary. In this article, we provide concepts and intermediate results of our work aimed at a long-term autonomous robotic system performing a plant monitoring task. based on notions from literature, we introduce a structured approach to defining long-term autonomy and report on the system we develop that meets this definition in practical experiments. Finally, we present intermediate results from simulation and discuss further avenues of research. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Agriculture

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Continuous Shortest Path Vector Field Navigation on 3D Triangular Meshes for Mobile robots

Continuous Shortest Path Vector Field Navigation on 3D Trian...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Puetz, Sebastian Wiemann, Thomas Piening, Malte Kleine Hertzberg, Joachim Osnabruck Univ Inst Comp Sci DFKIKnowledge Based Syst Plan Based Robot ControlGerman Res Ctr Artificia Osnabruck Germany

ISBN: (纸本)9781728190778

We present a highly efficient approach to compute continuous shortest path vector fields on arbitrarily shaped 3D triangular meshes for robot navigation in complex real-world outdoor environments. The continuity of the vector field allows to query the shortest distance, direction and geodesic path to the goal at any point within the mesh triangles, resulting in accurate paths. In order to avoid impassable areas, our wavefront propagation method runs on a modular extendable multilayer map architecture taking different geometric cost layers into account. We describe the mathematical foundation of the geodesic distances and continuous vector field computation and demonstrate the performance in real-world and multilevel environments on our campus with a tunnel, ramps and staircases, and in a difficult, steep forest area with a stone quarry. For reproducibility, we provide a ready-to-use ROS software stack as well as Gazebo simulations.

关键词： Three-dimensional displays Runtime Costs Navigation robot kinematics Computational modeling Forestry

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Object Anchoring for Autonomous robots Using the Spatio-Temporal-Semantic Environment Representation SEEREP 1

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46th German Conference on Artificial Intelligence (KI)

作者： Niemeyer, Mark Renz, Marian Hertzberg, Joachim German Res Ctr Artificial Intelligence Plan Based Robot Control Grp Osnabruck Germany Osnabruck Univ Knowledge Based Syst Grp Osnabruck Germany

ISBN: (数字)9783031426087

ISBN: (纸本)9783031426070;9783031426087

For single-plant specific weed regulation, robotic systems and agricultural machinery in general have to collect a large amount of temporal and spatial high-resolution sensor data. SEEREP, the Spatio-Temporal-Semantic Environment Representation, can be used to structure and manage such data more efficiently. SEEREP deals with the spatial, temporal and semantic modalities of data simultaneously and provides an efficient query interface for all three modalities that can be combined for high-level analyses. It supports popular robotic sensor data such as images and point clouds, as well as sensor and robot coordinate frames changing over time. This query interface enables high-level reasoning systems as well as other data analysis methods to handle partially unstructured environments that change over time, as for example agricultural environments. But the current methodology of SEEREP cannot store the result of the analysis methods regarding specific objects instances in the world. Especially the results of the anchoring problem which searches for a connection between symbolic and sub-symbolic data cannot be represented nor queried. Thus, we propose a further development of the SEEREP methodology in this paper: For a given object, we link the existing semantic labels in different datasets to a unique common instance, thereby enabling queries for datasets showing this object instance and with this enabling the efficient provision of datasets for object-centric analysis algorithms. Additionally, the results of those algorithms can be stored linked to the instance either by adding facts in a triple-store like manner or by adding further data linked to the instance, like a point, representing the position of the instance. We show the benefits of our anchoring approach in an agricultural setting with the use-case of single-plant specific weed regulation.

关键词： anchoring environment representation selective weeding

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COMPUTING ARBITRARILY LARGE MESHES WITH LEVEL-OF-DETAIL SUPPORT FOR CESIUM 3D TILES 7

COMPUTING ARBITRARILY LARGE MESHES WITH LEVEL-OF-DETAIL SUPP...

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7th International Workshop on LowCost 3D - Sensors, Algorithms, Applications

作者： Hillmann, Malte Igelbrink, Felix Wiemann, Thomas Osnabruck Univ Knowledge Based Syst Grp D-49080 Osnabruck Germany DFKI Niedersachsen Plan Based Robot Control D-49080 Osnabruck Germany

In this paper we present an approach to compute arbitrarily sized meshes of large scale environments. The meshes can be reconstructed from laser-scanned point clouds or existing high-resolution meshes. The algorithm automatically builds a level of detail hierarchy in the Cesium 3D Tiles format using an octree partition. The main contribution of this paper is a method that ensures that the generated meshes for each level-of-detail stage are computed in a consistent manner to minimize visual artifacts between different detail levels during rendering. Furthermore, both the reconstruction and simplification algorithm are designed to constrain the memory consumption, which enables to process even very large data sets on consumer-grade hardware. The export into the Cesium 3D Tiles format allows to render such large meshes efficiently in all web-based viewers that support this format. In our experiments we evaluate the method on different datasets and assess the visual quality during the rendering process and analyze the memory footprint as well as the runtime behaviour.

关键词： 3D Surface Reconstruction Mesh Simplification Level-of-Detail Rendering Web-based Visualization

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Tools for Visualizing, Annotating and Storing Triangle Meshes in ROS and RViz

Tools for Visualizing, Annotating and Storing Triangle Meshe...

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European Conference on Mobile robots (ECMR)

作者： Puetz, Sebastian Wiemann, Thomas Hertzberg, Joachim Univ Osnabruck Knowledge Based Syst Grp Osnabruck Germany German Res Ctr Artificial Intelligence Res Unit Plan Based Robot Control Osnabruck Germany

ISBN: (纸本)9781728136059

Polygonal maps for robotic applications are becoming increasingly popular, but are currently not effectively supported in the robot Operating System (ROS). In this paper, we introduce the Mesh Tools package consisting of message definitions, RViz plugins and a persistence layer to make the benefits of annotated polygonal maps available in ROS. These tools allow to publish, edit and inspect such maps within the existing ROS context. Our persistence layer efficiently loads and stores large mesh maps. We discuss two application areas as a proof-of-concept: Labeling of triangle clusters for semantic mapping and robot navigation on triangle meshes in a typical outdoor environment by integrating our tools into an existing navigation stack.

关键词： Three-dimensional displays Tools Two dimensional displays Octrees robots Semantics Navigation

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