CV Tag: Research Fund

  • Cyber Valley Research Fund’s self-supervised robot project

    Cyber Valley Research Fund’s self-supervised robot project

    Led by Prof. Dr. Jörg Stückler, Research Group Leader, and a dedicated team of researchers, the project, “Self-supervised learning of mobility affordances for vision-based navigation", has advanced the field of mobile robotics. They believe that mobile robots, whether in logistics or autonomous vehicles, should be able to properly adapt their navigation actions according to the surrounding environment. 

    The Cyber Valley Research Fund supported the project from March 2020 until its conclusion in October 2023. In this project, the team investigated novel approaches for adapting kinematic and dynamics models of wheeled mobile robots in a self-supervised way. The team’s goal was to develop modularized perception and motion control methods that allow dynamics models to learn through interaction with the environment. Stückler’s team created a method that uses camera images and inertial measurements to estimate the robot's motion.  

    They improved two types of robot platforms: one for indoor and one for outdoor use. Initially, they focused on a motion model for indoor wheeled robots controlled by setting target velocities. Then, they expanded this method to adjust parameters for a robot with car-like, steerable front wheels. Evaluating their online adaptation techniques showed better trajectory estimation and prediction accuracy compared to offline calibration or visual-inertial trajectory estimation without motion model information. 

    The Cyber Valley Research Fund, supported by six partners, has invested five million euros in fostering innovation and scientific excellence. Research groups were invited to submit project proposals, with ethical and societal considerations playing a crucial role in the evaluation process.   

    This project has yielded the following peer-reviewed publications: 

    • Li, H., Stueckler, J. Tracking 6-DoF Object Motion from Events and Frames. In Proc. of IEEE Int. Conf. on Robotics and Automation (ICRA), 2021. DOI: 10.1109/ICRA48506.2021.9561760 

    • Li, H., Stueckler, J. Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models. IEEE Robotics and Automation Letters (RA-L), 2022. DOI: 10.1109/LRA.2022.3169837 

    • Li, H., Stueckler, J. Online Calibration of a Single-Track Ground Vehicle Dynamics Model by Tight Fusion with Visual-Inertial Odometry. Accepted for IEEE International Conference on Robotics and Automation (2024). Preprint arXiv:2309.11148. 

    • Li, H., Stueckler, J. Observability Analysis of Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models abs/2204.06651, CoRR/arxiv, 2022 

  • Unveiling anomalies for safer connections

    Unveiling anomalies for safer connections

    Six partners within the Cyber Valley Community have generously contributed to the Cyber Valley Research Fund, totalling five million euros, to facilitate independent basic research. Research groups were invited to submit project proposals for the Research Fund, which the Cyber Valley Public Advisory Board evaluated, taking into account scientific excellence, as well as ethical and societal considerations.

    The research project’s core objective was anomaly detection within networked datasets, primarily focusing on identifying abnormal behavior across diverse network types, including social, communication, and transportation networks. The project thereby aimed to provide early warnings of potential threats or irregularities.

    The research introduced a novel approach that combined community structure with anomaly detection, enabling the identification of anomalies as edges that deviate from regular patterns. This innovative technique leveraged the structure of dynamic networks over time and inferred anomalies by integrating domain knowledge, such as community membership, into the analysis.

    The project yielded promising results, showcasing the model’s accuracy in capturing both community and anomaly structures, and its significant performance in predicting links within networks. The developed ideas and methodologies hold pertinent applications, particularly in fields such as cybersecurity and social network analysis, offering promising avenues for addressing critical challenges like fraud detection and network security enhancement. This includes applications such as uncovering fake users on social media platforms and detecting fraudulent activities in financial transactions.

    Furthermore, the research provided valuable insights into the dynamics of real-world networks by leveraging community structure alongside dynamic patterns of edge additions and deletions. Ultimately, the project not only advanced scientific understanding of network dynamics but also holds substantial potential for meaningful real-world impact. These discoveries herald new possibilities for addressing complex issues and enhancing the security and efficiency of various network systems.

    This project has yielded three peer reviewed publications:

    • “Anomaly detection and community detection in networks”, H. Safdari and C. De Bacco, J Big Data 9, 122, https://doi.org/10.1186/s40537-022-00669-1, 2022.
    • “Anomaly, reciprocity, and community detection in networks”, H. Safdari, M. Contisciani and C. De Bacco, Phys. Rev. Research 5, 033084, https://link.aps.org/doi/10.1103/PhysRevResearch.5.033084, 2023.
    • “Community detection and anomaly prediction in dynamic networks”, H. Safdari and C. De Bacco, work in progress, 2024. Paper and preprint expected to be submitted by April 2024.

    It also yielded two inventions:

  • Cyber Valley Research Fund Event

    Cyber Valley Research Fund Event

    Experts from industry and academia came together to discuss scientific advancement and to brainstorm future research paths. “The Cyber Valley Ecosystem continues to grow as a hotspot for innovation and research in AI and robotics”, Cyber Valley Scientific Coordinator Janell Lia-Breitmayer emphasized in her opening speech. This event lies at the heart of Cyber Valley, which originated from a collaboration between industry and academia to bring scientific excellence for the benefit of society. 

    Cyber Valley Research Fund Initiatives 

    The first cornerstone of the symposium was the presentation of five independent research initiatives that have thrived under the support of the Cyber Valley Research Fund. Prof. Dr. Jörg-Dieter Stückler, who heads the Embodied Vision Research Group, showed how the use of an adaptive dynamics model can improve the trajectory estimation and prediction of a robot. By optimizing its parameters in a self-supervised manner, the robot can adapt to variations in system dynamics and plan a more efficient path through unknown terrain. 

    In a second research project supervised by Stückler under the Cyber Valley iniative, the group combined extended Kalman filtering with a differentiable physics simulator to estimate trajectories of 3D objects. In addition to reconstructing an object’s shape and pose, the model is able to infer physical properties, such as velocity and friction, from RGB-D images. This information can be used to simulate physically plausible trajectories of sliding and colliding objects.

    Subsequently, two projects of the Physics for Inference and Optimization Research Group led by Caterina De Bacco were presented. PhD student Martina Contisciani discussed advancements in network reconstruction from data. By relaxing assumptions about the conditional independence of edges, she enhances the detection of communities and clusters. In addition, her probabilistic model is able to infer the reliability of nodes, which is particularly valuable in reconstructing networks from social sciences data, where conflicting reports from multiple individuals are common.

    Postdoctoral researcher Dr. Hadiseh Safdari continued the discourse by looking at anomaly detection within networks. To identify parts of the network that deviate from the norm, she and her colleagues use a probabilistic generative model that compares the observed network with synthetic data, generated based on assumptions about community membership and reciprocity. Safdari highlighted applications such as uncovering fake users on social media platforms and detecting fraudulent activities in financial transactions. 

    Prof. Dr. Georg Martius, leader of the Autonomous Learning Research Group, explored the fusion of combinatorial algorithms and machine learning. He presented a method that implements a backward pass for combinatorial solvers with linear objective functions, allowing them to be used as building blocks in deep learning pipelines. This novel approach exploits both the reliability and efficiency of discrete optimization and the flexibility of deep learning, resulting in architectures that can solve tasks beyond the capabilities of conventional neural networks.

    After the lunch break, Rebecca Beiter's presentation on public engagement for the industry resonated as a powerful call for a modern communication paradigm. Engaging with the public entails more than just information dissemination, she emphasized — it requires active and ongoing interaction with all relevant knowledge actors, including politicians, journalists, NGOs, start-ups, and educational institutions. Beiter underlined the evolution of public engagement, defining it as a field, a practice, and above all, an attitude: "It will change the culture in which you work!”.

    Cyber Valley Founding Partner Industry Research 

    In the final round of presentations, representatives from Porsche, Amazon, and Fraunhofer shared insights into industry research. Dr.-Ing Bruno Kistner, Head of Data-Driven Development at Porsche AG, highlighted Porsche's use of AI in customer-centric applications, exemplified by intelligent climate control among its smart products and services. He outlined Porsche's AI-driven optimization of production processes, ensuring quality and support to employees throughout the design and production phases.

    Amazon Applied Principal Scientist, Dr. Betty Mohler-Tesch, demonstrated how Amazon aims to enhance customer experience with innovation, such as virtual avatars and AI-powered personal shoppers. Stressing the importance of inclusivity, she remarked: “Fashion is for everyone – you can’t avoid putting clothes on in the morning”. Her research group aims to improve the generation of realistic three-dimensional human avatars. Their goal is to enable customers to digitally try on clothes and order custom-fit garments, thereby reducing stress and lowering return rates. 

    Fraunhofer IAO researcher Ravi Kanth Kosuru spoke about Fraunhofer’s research in applied neurocognitive systems. Aiming to promote human-machine partnership, the group employs neuro-technology, such as EEG systems, to measure cognitive and emotional states of users. Their work involves refining brain-computer interfaces to enable the interpretation of brain signals, data classification, and automatic error detection.

    In the final presentation, Fraunhofer IPA Researcher Tim Nickel presented model-free 3D bin packing as an innovative solution for the growing need for warehouse automation. Physically demanding yet mentally unstimulating, packaging is prone to error, making it ideal for automation. Nickel presented a robot system capable of densely packing arbitrarily shaped objects with ad hoc planning. Unlike static approaches, this method enables unexpected circumstance, such as rolling or shifting of objects, without collision.

    The evening was rounded off by a lively networking session, which included discussions on open research questions and potential future collaborations.

    For any questions regarding the Cyber Valley Research Fund, please contact: 

  • Cyber Valley Meet-up

    Cyber Valley Meet-up

    Wir laden euch herzlich zu diesem entspannten Treffen für alle Start-ups, Forschungsgruppen und Doktorand:innen ein!

    Cyber Valley Geschäftsführerin Rebecca C. Reisch wird eine kurze Einführung über Cyber Valley, seine Mission, das Team und die Zukunftspläne geben. Danach werden wir eine informelle Fragerunde abhalten, in der ihr uns bei Pizza, Salat und einem kühlen Getränk eurer Wahl alles über Cyber Valley fragen können. Außerdem würden wir gerne von euch wissen, welche Erwartungen ihr an Cyber Valley habt.

     

    Wann?

    Mittwoch, 7. Dezember 2022. 17:30–20:00 Uhr


    Wo?

    Max-Planck-Institut für Intelligente Systeme, Tübingen. Lounge im Erdgeschoss.

     

    Anmeldung

    Wir freuen uns darauf, euch zu treffen sowie mit euch bei etwas zu essen, zu trinken und anregende Gespräche zu führen. 

    Anmeldung

    Die Veranstaltung ist kostenlos und jede:r kann einfach vorbei kommen. Eine Anmeldung über den Button unten hilft uns allerdings, damit wir genug Pizza für alle bestellen. Bei Fragen und zur Anmeldung von Pitches wende dich gerne an: Oliwia Gust, Cyber Valley Event Manager, oliwia.gust@cyber-valley.de

    Wir freuen uns darauf, Sie kennenzulernen und gemeinsam etwas zu essen, zu trinken und anregende Gespräche zu führen! Kommen Sie einfach vorbei.

    Kommt einfach vorbei – 

     

    Bei Fragen wendet ihr euch bitte an Oliwia Gust, Cyber Valley Event Managerin: oliwia.gust@cyber-valley.de