Fraunhofer-Publica
The Fraunhofer-Publica has been successfully documenting the research results of the Fraunhofer-Gesellschaft for over 30 years. The platform enables the collaborative linking of research-relevant objects and disseminates within the international scientific community.
The Fraunhofer-Publica thus fulfils its responsibility to promote the transfer of knowledge and know-how to industry and society.
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Research outputs
As an application-oriented research organisation, Fraunhofer aims to conduct highly innovative and solution-oriented research - for the benefit of society and to strengthen the German and European economy.
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Projects
Fraunhofer is tackling the current challenges facing industry head on. By pooling their expertise and involving industrial partners at an early stage, the Fraunhofer Institutes involved in the projects aim to turn original scientific ideas into marketable products as quickly as possible.
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Researchers
Scientific achievement and practical relevance are not opposites - at Fraunhofer they are mutually dependent. Thanks to the close organisational links between Fraunhofer Institutes and universities, science at Fraunhofer is conducted at an internationally first-class level.
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Institutes
The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Institutes and research facilities work under its umbrella at various locations throughout Germany.
Recent Additions
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PublicationForce-Sensor-Free Implementation of a Hybrid Position - Force Control for Overconstrained Cable-Driven Parallel Robots( 2024)This paper proposes a hybrid position–force control strategy for overconstrained cable-driven parallel robots (CDPRs). Overconstrained CDPRs have more cables (m) than degrees of freedom (n), and the idea of the proposed controller is to control n cables in length and the other (Formula presented.) ones in force. Two controller implementations are developed, one using the motor torque and one using the motor following-error in the feedback loop for cable force control. A friction model of the robot kinematic chain is introduced to improve the accuracy of the cable force estimation. Compared to similar approaches available in the literature, the novelty of the proposed control strategy is that it does not rely on force sensors, which reduces the hardware complexity and cost. The developed control scheme is compared to classical methods that exploit force sensors and to a pure inverse kinematic controller. The experimental results show that the new controller provides good tracking of the desired cable forces, maintaining them within the given bounds. The positioning accuracy and repeatability are similar those obtained with the other controllers. The new approach also allows an online switch between position and force control of cables.
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PublicationEnzyme-Assisted Circular Additive Manufacturing as an Enabling Technology for a Circular Bioeconomy - A Conceptual Review( 2024)Additive manufacturing (AM) is a decisive element in the sustainable transformation of technologies. And yet its inherent potential has not been fully utilized. In particular, the use of biological materials represents a comparatively new dimension that is still in the early stages of deployment. In order to be considered sustainable and contribute to the circular economy, various challenges need to be overcome. Here, the literature focusing on sustainable, circular approaches is reviewed. It appears that existing processes are not yet capable of being used as circular economy technologies as they are neither able to process residual and waste materials, nor are the produced products easily biodegradable. Enzymatic approaches, however, appear promising. Based on this, a novel concept called enzyme-assisted circular additive manufacturing was developed. Various process combinations using enzymes along the process chain, starting with the preparation of side streams, through the functionalization of biopolymers to the actual printing process and post-processing, are outlined. Future aspects are discussed, stressing the necessity for AM processes to minimize or avoid the use of chemicals such as solvents or binding agents, the need to save energy through lower process temperatures and thereby reduce CO2 consumption, and the necessity for complete biodegradability of the materials used.
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PublicationExplainability and Interpretability in Electric Load Forecasting Using Machine Learning Techniques - A Review( 2024)Electric Load Forecasting (ELF) is the central instrument for planning and controlling demand response programs, electricity trading, and consumption optimization. Due to the increasing automation of these processes, meaningful and transparent forecasts become more and more important. Still, at the same time, the complexity of the used machine learning models and architectures increases. Because there is an increasing interest in interpretable and explainable load forecasting methods, this work conducts a literature review to present already applied approaches regarding explainability and interpretability for load forecasts using Machine Learning. Based on extensive literature research covering eight publication portals, recurring modeling approaches, trends, and modeling techniques are identified and clustered by properties to achieve more interpretable and explainable load forecasts. The results on interpretability show an increase in the use of probabilistic models, methods for time series decomposition and the use of fuzzy logic in addition to classically interpretable models. Dominant explainable approaches are Feature Importance and Attention mechanisms. The discussion shows that a lot of knowledge from the related field of time series forecasting still needs to be adapted to the problems in ELF. Compared to other applications of explainable and interpretable methods such as clustering, there are currently relatively few research results, but with an increasing trend.
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PublicationROBUST: 221 bugs in the Robot Operating System( 2024)As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.
Most viewed
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PublicationMeasurement of Local Recombination Activity in High Diffusion Length Semiconductors( 2023)
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