Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB

Filters

4
Reset filters

Settings
Now showing 1 - 10 of 976
  • 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
    Chance-Constrained Optimal Design of PV-Based Microgrids under Grid Blackout Uncertainties
    ( 2024)
    Alramlawi, Mansour
    ;
    Li, Pu
    A grid blackout is an intractable problem with serious economic consequences in many developing countries. Although it has been proven that microgrids (MGs) are capable of solving this problem, the uncertainties regarding when and for how long blackouts occur lead to extreme difficulties in the design and operation of the related MGs. This paper addresses the optimal design problem of the MGs considering the uncertainties of the blackout starting time and duration utilizing the kernel density estimator method. Additionally, uncertainties in solar irradiance and ambient temperature are also considered. For that, chance-constrained optimization is employed to design residential and industrial PV-based MGs. The proposed approach aims to minimize the expected value of the levelized cost of energy (𝐿𝐶𝑂𝐸), where the restriction of the annual total loss of power supply (𝑇𝐿𝑃𝑆) is addressed as a chance constraint. The results show that blackout uncertainties have a considerable effect on calculating the size of the MG’s components, especially the battery bank size. Additionally, it is proven that considering the uncertainties of the input parameters leads to an accurate estimation for the LCOE and increases the MG reliability level.
  • Publication
    Designing User Interfaces for Automated Driving: A Simulator Study on Individual Information Preferences
    ( 2024)
    Driesen Micklitz, Tim
    ;
    Fellmann, Michael
    ;
    Röcker, Carsten
    Automated Driving (AD) can free users from driving and create time for their disposal. However, since manufacturers increasingly target a wide customer range with AD, such systems and their User Interfaces (UI) must accommodate different user characteristics and preferences. This paper aims to analyze the effects of individual characteristics on the information preferences in UIs for surrounding road infrastructure (for instance, lane markings or traffic signs) and system limits describing hindering factors for AD (for instance, construction sites or unsuitable weather conditions). To do so, we performed a driving simulator study with 43 participants. Results show that users with a more positive attitude towards technology prefer more infrastructure information. Furthermore, users familiar with Automatic Cruise Control prefer less system limit information, while higher experience with Steering Assists relates to higher preference in this regard. These findings add concrete mechanisms to the theory of personalized AD UIs and inform product development on how to create more personalized user experiences. By this, we aim to address challenges regarding the acceptance, adoption, and usage of AD.
  • Publication
    Temperature investigation of low SWaP thulium-doped fiber lasers
    ( 2024)
    Panitzek, Dieter
    ;
    Romano, Clément
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    We investigate the temperature dependence of an in-band core-pumped thulium-doped fiber laser with a low SWaP (size, weight, and power) architecture. The temperature investigation is carried out both experimentally and numerically by a simulation model. We demonstrate experimentally that the investigated setup is resistant for temperatures till 353 K. In addition, we explain the observed behavior by considering the temperature depended spectroscopic parameters of thulium-doped silica fibers. Finally, a numerical investigation is carried out for higher temperatures up to 573 K and higher output powers up to 12 W as well as for different wavelengths and show that the considered fiber lasers works still efficient at these temperature ranges. We show the reliability of the considered thulium-doped fiber laser architecture for applications in harsh environment.
  • Publication
    Security Fence Inspection at Airports Using Object Detection
    ( 2024)
    Friederich, Nils
    ;
    Specker, Andreas
    ;
    Beyerer, Jürgen
    To ensure the security of airports, it is essential to protect the airside from unauthorized access. For this pur-pose, security fences are commonly used, but they require regular inspection to detect damages. However, due to the growing shortage of human specialists and the large man-ual effort, there is the need for automated methods. The aim is to automatically inspect the fence for damage with the help of an autonomous robot. In this work, we explore object detection methods to address the fence inspection task and localize various types of damages. In addition to evaluating four State-of-the-Art (SOTA) object detection models, we analyze the impact of several design criteria, aiming at adapting to the task-specific challenges. This in-cludes contrast adjustment, optimization of hyperparameters, and utilization of modern backbones. The experimental results indicate that our optimized You Only Look Once v5 (YOLOv5) model achieves the highest accuracy of the four methods with an increase of 6.9% points in Average Precision (AP) compared to the baseline. Moreover, we show the real-time capability of the model. The trained models are published on GitHub: hups://github.com/IN-Friederichlairport_fence_inspection.
  • Publication
  • Publication
    2nd Workshop on Maritime Computer Vision (MaCVi) 2024: Challenge Results
    ( 2024)
    Kiefer, Benjamin
    ;
    Žust, Lojze
    ;
    Kristan, Matej
    ;
    Perš, Janez
    ;
    Teršek, Matija
    ;
    Wiliem, Arnold
    ;
    Messmer, Martin
    ;
    Yang, Cheng
    ;
    Huang, Wei
    ;
    Jiang, Zhongyu
    ;
    Kuo, Cheng-liang
    ;
    Mei, Jie
    ;
    Hwang, Jenq-neng
    ;
    Stadler, Daniel
    ;
    Sommer, Lars Wilko
    ;
    Huang, Kaer
    ;
    Aiguo Zheng
    ;
    Chong, Weitu
    ;
    Lertniphonphan, Kanokphan
    ;
    Xie, Lie-jun
    ;
    Chen, Feng
    ;
    Li, Jian
    ;
    Wang, Zhepeng
    ;
    Zedda, Luca
    ;
    Loddo, Andrea
    ;
    Di Ruberto, Cecilia
    ;
    Vu, Tuan-Anh
    ;
    Hai, Nguyen
    ;
    Ha, Van Sang
    ;
    Tien, Dung Pham
    ;
    Yeung, Kit Ling
    ;
    Feng, Yuan
    ;
    Thien, Nguyen Thanh
    ;
    Tian, Lixin
    ;
    Kuan, Sheng-Yao
    ;
    Ho, Yuan-Hao
    ;
    Bueno Rodriguez, Angel
    ;
    Carrillo-Perez, Borja
    ;
    Klein, Alexander
    ;
    Alex, Antje
    ;
    Steiniger, Yannik
    ;
    Sattler, Felix
    ;
    Solano-carrillo, Edgardo
    ;
    Fabijanić, Matej
    ;
    Šumunec, Magdalena
    ;
    Kapetanović, Nadir
    ;
    Michel, Andreas
    ;
    Groß, Wolfgang
    ;
    Weinmann, Martin
    The 2nd Workshop on Maritime Computer Vision (MaCVi) 2024 addresses maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned Surface Vehicles (USV). Three challenges categories are considered: (i) UAV-based Maritime Object Tracking with Re-ideruification, (ii) USV-based Maritime Obstacle Segmentation and Detection, (iii) USV-based Maritime Boat Tracking. The USV-based Maritime Obstacle Segmentation and Detection features three sub-challenges, including a new embedded challenge addressing efficicent inference on real-world embedded devices. This report offers a comprehensive overview of the findings from the challenges. We provide both statistical and qualitative analyses, evaluating trends from over 195 submissions. All datasets, evaluation code, and the leaderboard are available to the public at https://macvi.org/workshop/macvi24.
  • Publication
    Reinforcement Learning for Two-Stage Permutation Flow Shop Scheduling - A Real-World Application in Household Appliance Production
    ( 2024)
    Müller, Arthur
    ;
    Grumbach, Felix
    ;
    Kattenstroth, Fiona
    Solving production scheduling problems is a difficult and indispensable task for manufacturers with a push-oriented planning approach. In this study, we tackle a novel production scheduling problem from a household appliance production at the company Miele & Cie. KG, namely a two-stage permutation flow shop scheduling problem (PFSSP) with a finite buffer and sequence-dependent setup efforts. The objective is to minimize idle times and setup efforts in lexicographic order. In extensive and realistic data, the identification of exact solutions is not possible due to the combinatorial complexity. Therefore, we developed a reinforcement learning (RL) approach based on the Proximal Policy Optimization (PPO) algorithm that integrates domain knowledge through reward shaping, action masking, and curriculum learning to solve this PFSSP. Benchmarking of our approach with a state-of-the-art genetic algorithm (GA) showed significant superiority. Our work thus provides a successful example of the applicability of RL in real-world production planning, demonstrating not only its practical utility but also showing the technical and methodological integration of the agent with a discrete event simulation (DES). We also conducted experiments to investigate the impact of individual algorithmic elements and a hyperparameter of the reward function on the overall solution.
  • Publication
    Investigation of the polymer material perforation time: comparison between two fiber laser wavelengths
    ( 2024)
    Romano, Clément
    ;
    Ritt, Gunnar
    ;
    Henrichsen, Michael
    ;
    Eichhorn, Marc
    ;
    Kieleck, Christelle
    This study investigated the perforation time of polyamide 6.6 using fiber lasers at two different wavelengths: 1070 and 1943 nm. The novelty of this research lies in the comparison of perforation times at equivalent laser irradiances on the polymer sample with two different colors of polyamide 6.6: natural and black. The results revealed that, at comparable irradiance levels and beam diameters, the 1943 nm laser source perforated the polyamide 6.6 sample faster than the 1070 nm laser source. The difference in perforation time was found to be significantly higher for natural-colored polyamide 6.6 compared to black-colored polyamide 6.6. These findings suggest that, for material processing of polyamide 6.6, especially in terms of perforation, the use of 2 μm laser sources should be privileged over 1 μm laser sources.
  • Publication
    Pattern Recognition. Introduction, Features, Classifiers and Principles
    (De Gruyter, 2024)
    Beyerer, Jürgen
    ;
    Hagmanns, Raphael
    ;
    Stadler, Daniel
    The book offers a thorough introduction to Pattern Recognition aimed at master and advanced bachelor students of engineering and the natural sciences. Besides classification - the heart of Pattern Recognition - special emphasis is put on features: their typology, their properties and their systematic construction. Additionally, general principles that govern Pattern Recognition are illustrated and explained in a comprehensible way. Rather than presenting a complete overview over the rapidly evolving field, the book clarifies the concepts so that the reader can easily understand the underlying ideas and the rationale behind the methods. For this purpose, the mathematical treatment of Pattern Recognition is pushed so far that the mechanisms of action become clear and visible, but not farther. Therefore, not all derivations are driven into the last mathematical detail, as a mathematician would expect it. Ideas of proofs are presented instead of complete proofs. From the authors’ point of view, this concept allows to teach the essential ideas of Pattern Recognition with sufficient depth within a relatively lean book.