Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

Filters

4
Reset filters

Settings
Now showing 1 - 10 of 4330
  • Publication
    Simulation of the reflection of a high energy laser beam at the sea surface for hazard and risk analyses
    ( 2024-04-10)
    Schwenger, Frederic
    ;
    Azarian, Adrian
    ;
    Henrichsen, Michael
    The application of a high energy laser beam in a maritime scenario necessitates a laser safety concept to prevent injury to personnel or uninvolved third parties from uncontrolled reflections of laser light from the sea surface. Therefore, it is crucial to have knowledge of the amount and direction of reflected laser energy, which varies statistically and depends largely on the dynamics of the wavy sea surface. These dynamics are primarily influenced by wind speed, wind direction, and fetch. An analytical model is presented for calculating the time-averaged spatial intensity distribution of the laser beam reflected at the dynamic sea surface. The model also identifies the hazard areas inside which laser intensities exceed a fixed exposure limit. Furthermore, as far as we know, our model is unique in its ability to calculate the probabilities of potentially eye-damaging glints for arbitrary observer positions, taking into account the slope statistics of gravity waves. This is a critical first step toward an extensive risk analysis. The simulation results are presented on a hemisphere of observer positions with fixed radii from the laser spot center. The advantage of the analytical model over our numeric (dynamic) model is its fast computation time. A comparison of the results of our new analytical model with those of the previous numerical model is presented.
  • Patent
    Network node for a non-detectable laser communication system
    ( 2024-02-07)
    Kieleck, Christelle
    ;
    Eichhorn, Marc
    ;
    Rudow, Oliver
    ;
    Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V.
    ;
    Hensoldt Sensors GmbH
    A network node (120) for a non-detectable laser communication system (100), wherein the laser communication system (100) is configured to send to the network node (120) at least one laser beam (10), comprises a reflector device (123), configured to generate, by a reflection of the laser beam (10), a reflected laser beam (20), and a modulator device (125), configured to provide a modulation of the reflected laser beam (20).
  • Publication
    Quantum computer-aided job scheduling for storage and retrieval systems
    ( 2024)
    Windmann, Stefan
    In this paper, a quantum computer-aided approach to job scheduling for automated storage and retrieval systems is introduced. The approach covers application cases, where various objects need to be transported between storage positions and the order of transport operations can be freely chosen. The objective of job scheduling is to arrange the transport operations in a sequence, where the cumulative costs of the transport operations and empty runs between subsequent transport operations are minimized. The scheduling problem is formulated as an asymmetric quadratic unconstrained binary optimization (QUBO) problem, in which the transport operations are modeled as nodes and empty runs are modeled as edges, with costs assigned to each node and each edge. An Quantum Approximate Optimization Algorithm (QAOA) is used to solve the QUBO. Evaluations of the quantum computer-aided job scheduling approach have been conducted on the IBM Q System One quantum computer in Ehningen. In particular, the running time for the solution of the QUBO has been investigated, as well as the scalability of the approach with respect to the required number of qubits.
  • Publication
    Regression via causally informed Neural Networks
    ( 2024)
    Youssef, Shahenda
    ;
    Doehner, Frank
    ;
    Beyerer, Jürgen
    Neural Networks have been successful in solving complex problems across various fields. However, they require significant data to learn effectively, and their decision-making process is often not transparent. To overcome these limitations, causal prior knowledge can be incorporated into neural network models. This knowledge improves the learning process and enhances the robustness and generalizability of the models. We propose a novel framework RCINN that involves calculating the inverse probability of treatment weights given a causal graph model alongside the training dataset. These weights are then concatenated as additional features in the neural network model. Then incorporating the estimated conditional average treatment effect as a regularization term to the model loss function, the potential influence of confounding variables can be mitigated, leading to bias minimization and improving the neural network model. Experiments conducted on synthetic and benchmark datasets using the framework show promising results.
  • Publication
    Attribute-Based Person Retrieval in Multi-Camera Networks
    ( 2024)
    Specker, Andreas
    ;
    Beyerer, Jürgen
    Attribute-based person retrieval is a crucial component in various realworld applications, including surveillance, retail, and smart cities. Contrary to image-based person identification or re-identification, individuals are searched for based on descriptions of their soft biometric attributes, such as gender, age, and clothing colors. For instance, attribute-based person retrieval enables law enforcement agencies to efficiently search enormous amounts of surveillance footage gathered from multi-camera networks to locate suspects or missing persons. This thesis presents a novel deep learning framework for attribute-based person retrieval. The primary objective is to research a holistic approach that is suitable for real-world applications. Therefore, all necessary processing steps are covered. Pedestrian attribute recognition serves as the base framework to address attribute-based person retrieval in this thesis. Various design characteristics of pedestrian attribute recognition approaches are systematically examined toward their suitability for attribute-based person retrieval. Following this analysis, novel techniques are proposed and discussed to further improve the performance. The PARNorm module is introduced to normalize the model’s output logits across both the batch and attribute dimensions to compensate for imbalanced attributes in the training data and improve person retrieval performance simultaneously. Strategies for video-based pedestrian attribute recognition are explored, given that videos are typically available instead of still images. Temporal pooling of the backbone features over time proves to be effective for the task. Additionally, this approach exhibits faster inference than alternative techniques. To enhance the reliability of attributebased person retrieval rankings and address common challenges such as occlusions, an independent hardness predictor is proposed that predicts the difficulty of recognizing attributes in an image. This information is utilized to remarkably improve retrieval results by down-weighting soft biometrics with an increased chance of classification failure. Additionally, three further enhancements to the retrieval process are investigated, including model calibration based on existing literature, a novel attribute-wise error weighting mechanism to balance the attributes’ influence on retrieval results, and a new distance measure that relies on the output distributions of the attribute classifier. Meaningful generalization experiments on pedestrian attribute recognition and attribute-based person retrieval are enabled for the first time. For this purpose, the UPAR dataset is proposed, which contributes 3.3 million binary annotations to harmonize semantic attributes across four existing datasets and introduces two evaluation protocols. Moreover, a new evaluation metric is suggested that is tailored to the task of attribute-based person retrieval. This metric evaluates the overlap between query attributes and the attributes of the retrieved samples to obtain scores that are consistent with the human perception of a person retrieval ranking. Combining the proposed approaches yields substantial improvements in both pedestrian attribute recognition and attribute-based person retrieval. State-of-the-art performance is achieved concerning both tasks and existing methods from the literature are surpassed. The findings are consistent across both specialization and generalization settings and across the well-established research datasets. Finally, the entire processing pipeline, from video feeds to the resulting retrieval rankings, is outlined. This encompasses a brief discussion on the topic of multi-target multi-camera tracking.
  • Publication
    How to Indicate AI at Work on Vehicle Dashboards: Analysis and Empirical Study
    ( 2024)
    Rössger, Peter
    ;
    Acevedo, Cristián
    ;
    Bottesch, Miriam
    ;
    Nau, Samuel
    ;
    Stricker, Tobias
    ;
    Diederichs, Frederik
    The KARLI project aims to create an adaptive AI system for future vehicles. It’s focusing on motion sickness, level-compliant driver behavior, and AI-HMI (artificial intelligence human-machine Interface). The project explores making AI activities visible through avatars, aiming to enhance user experiences and empower users to understand and influence AI decisions for a positive interaction with technology. AI representations in HMIs range from non-representational to realistic, introducing a classification that includes "HMI-integrated." The analysis explores AI representations in vehicle HMIs, citing Nio's Nomi and Waymo's ride service as examples. AI depictions in films, ranging from abstract (HAL 9000) to realistic (Ava from "Ex Machina"), are examined. The KARLI project aims to differentiate itself by explicitly representing AI activity on screens in non-fictional and automotive contexts. Pros and cons of different levels of abstraction in AI avatars are made. A study predominantly involving females and younger individuals, showing a positive attitude toward AI was conducted. Three design variants of the avatar were tested in a comparative laboratory study. All tested designs received negative Net Promoter Scores, with the abstract figurative design rated the best and the figurative design the creepiest. All designs scored low on "Intention to Use," indicating participants’ reluctance, and "Product Loyalty" echoed this sentiment. A final design was created based on the results of analysis and study.
  • Publication
    High-power thulium-doped fiber MOPA emitting at 2036 nm
    ( 2024)
    Romano, Clément
    ;
    Panitzek, Dieter
    ;
    Lorenz, Dominik
    ;
    Forster, Patrick
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    An all-fiber laser system is presented with a simple MOPA configuration composed of a seed laser followed by a one-stage high-power amplifier. The seed delivers 10 W of output power at 2036 nm. The high-power amplifier operates with a high slope efficiency of 59 %. An output power of 937 W is demonstrated with a close to diffraction limited beam quality. No nonlinear effects were observed.
  • Publication
    A survey of the state of the art in sensor-based sorting technology and research
    ( 2024)
    Maier, Georg
    ;
    Gruna, Robin
    ;
    Längle, Thomas
    ;
    Beyerer, Jürgen
    Sensor-based sorting describes a family of systems that enable the removal of individual objects from a material stream. The technology is widely used in various industries such as agriculture, food, mining, and recycling. Examples of sorting tasks include the removal of fungus-infested grains, the enrichment of copper content in copper mining or the sorting of plastic waste according to the type of plastic. Sorting decisions are made based on information acquired by one or more sensors. A particular strength of the technology is the flexibility in sorting decisions, which is achieved by using various sensors and programming the data analysis. However, a comprehensive understanding of the process is necessary for the development of new sorting systems that can address previously unresolved tasks. This survey is aimed at innovative researchers and practitioners who are unfamiliar with sensor-based sorting or have only encountered certain aspects of the overall process. The references provided serve as starting points for further exploration of specific topics.
  • Publication
    Bridging the Gap Between IDS and Industry 4.0 - Lessons Learned and Recommendations for the Future
    ( 2024)
    Alexopoulos, Kosmas
    ;
    Bakopoulos, Emmanouil
    ;
    Larrinaga Barrenechea, Felix
    ;
    Castellvi, Silvia
    ;
    Firouzi, Farshad
    ;
    Luca, Gabriele de
    ;
    Maló, Pedro
    ;
    Marguglio, Angelo
    ;
    Meléndez, Francisco
    ;
    Meyer, Tom
    ;
    Orio, Giovanni di
    ;
    Pethig, Florian
    ;
    Ruíz, Jesús
    ;
    Treichel, Tagline
    ;
    Usländer, Thomas
    ;
    Volz, Friedrich
    ;
    Watson, Kym
    ;
    Stojanovic, Ljiljana
    The Plattform Industrie 4.0 (PI4.0) and the International Data Spaces Association (IDSA) are two independent, parallel initiatives with clear focuses. While PI4.0 addresses communication and interaction between networked assets in a smart factory and/or supply chain across an asset or product lifecycle, IDSA is about a secure, sovereign system of data sharing in which all stakeholders can realize the full value of their data. Since data sharing between companies requires both interoperability and data sovereignty, the question emerges regarding the feasibility and rationality of integrating the expertise of PI4.0 and IDSA. The IDS-Industrial Community (IDS-I) is an extension of IDSA whose goal is to strengthen the cooperation between IDSA and PI4.0. Two fields of expertise could be combined: The Platform's know-how in the area of Industrie 4.0 (I4.0) and the IDSA's expertise in the areas of data sharing ecosystems and data sovereignty. In order to realize this vision, many aspects have to be taken into account, as there are discrepancies on multiple levels. Specifically, at the reference architecture level, we have the RAMI4.0 model on the PI4.0 side and the IDS Reference Architecture Model (IDS-RAM) on the IDSA side. While the existing I4.0 and IDS specifications are incompatible e.g. in terms of models (i.e., the AAS metamodel and the IDS information model) and APIs, there is also the issue of interoperability between I4.0 and IDS solutions. This position paper aims to bridge the gap between IDS and PI4.0 by not only analyzing how their existing concepts, tools, etc. have been "connected" in different contexts. Rather, this position paper makes recommendations on how different technologies could be combined in a generic way, independent of the concrete implementation of IDS and/or I4.0 relevant technology components. This paper could be used by both the IDS and I4.0 communities to further improve their specifications, which are still under development. The lessons learned and feedback from the initial joint use of technology components from both areas could provide concrete guidance on necessary improvements that could further strengthen or extend the specifications. Furthermore, it could help to promote the IDS architecture and specifications in the industrial production and smart manufacturing community and extend typical PI4.0 use cases to include data sovereignty by incorporating IDS aspects.
  • Publication
    Tiled aperture coherent beam combination of 2 μm fiber lasers
    ( 2024)
    Romano, Clément
    ;
    Panitzek, Dieter
    ;
    Pradat-Peyre, Gabriel
    ;
    Milcent, Simon
    ;
    Uthayakumar, Jashaani
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    Exceeding the multi-kW power level with thulium-doped fiber lasers has not been achieved using a single thulium-doped fiber laser. One solution to overcome this limit is the coherent beam combination. We focus on an active phase control with tiled aperture configuration. The setup consists in an amplified seed laser split in three channels. These channels are controlled in phase and amplified again before being launched free space and combined. A SPGD algorithm controls the channel’s phase to provide combination. Rise time below 0.5 ms were achieved with a residual amplitude noise lower than λ/30.