Working Group

Human in Command

The "Human in Command" research group at Aalen University of Applied Sciences is dedicated to researching and developing concepts for the use of artificial intelligence (AI) in the future world of work. The group’s overarching goal is to create innovative solutions that enable efficient and harmonious collaboration between humans and machines. A particular focus is placed on developing systems that are not only technically advanced but also user-friendly and ethically sound.

The three pillars of “Human in Command”
Research Projects
AI Research
Technology in Everyday Life
Practical Training
Humans on the AI Command Bridge: Our Research Lab at Aalen University of Applied Sciences
Team
News
Publications

Control and Cooperation in the Age of AI

The introduction and increased use of algorithms based on artificial intelligence are impacting governments, the economy, and individuals. Against this backdrop, the question arises regarding human control over—and the controllability of—automated systems. The challenge lies in developing AI systems in the future where humans and machines work productively together and understand one another.

Research on the Opportunities and Risks of Using Artificial Intelligence
Interdisciplinary research across various fields to holistically analyze complex issues and develop innovative solutions by combining expert knowledge from different disciplines
Industry-oriented research and practice-oriented scientific studies directly tailored to the needs and challenges of industry
Robotics laboratory for the development of intelligent automation solutions

The three pillars of “Human in Command”

Participatory Design

AI and robotics systems are developed in collaboration with those who will use them.

Situational Awareness

Systems based on the Human-in-Command principle must ensure that the people working with them know what the system is doing at all times.

Meaningful Control

Human-in-Command systems must be controllable and manageable in a way that makes sense to people.

Ongoing Projects

With the RePAIR project—“Remanufacturing with Personalized Adaptive Intelligent Robotic Assistance”—Aalen University of Applied Sciences is developing a forward-looking concept for the sustainable refurbishment of electronic products. The focus is on the use of hybrid intelligence—the combination of human expertise and artificial intelligence.

The RecycleBot project, funded by the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety, and Consumer Protection, launched in March 2023 with the goal of significantly increasing the recycling rate of plastic-based packaging and commercial waste. Through the use of collaborative robotics and AI-supported sorting processes, waste is to be directed to the appropriate recycling streams. This enables more efficient recycling and reduces the consumption of scarce resources—such as raw materials and energy—that would otherwise be required for the production of new materials. At the same time, the project helps protect the environment by reducing waste volumes and emissions.

The RewitAl project focuses on the sustainable recycling of waste plastics from sports facilities, particularly artificial turf surfaces. The goal is to develop environmentally friendly recycling processes and to research alternatives such as bioplastics. The project is receiving approximately 2.2 million euros in funding through 2027 from the State of Baden-Württemberg and the European Regional Development Fund (ERDF). In addition to Aalen University of Applied Sciences, Furtwangen University of Applied Sciences and Pforzheim University of Applied Sciences, as well as numerous partners from industry, politics, and sports, are also involved.

ILUSIK is creating a solution that turns traditional intralogistics processes on their head. The goal is to achieve cost savings of 20–30% by having goods autonomously capture information, interact with users, and generate data from which AI derives further optimization potential. The technology is highly mobile and ready for immediate use without requiring complex configuration. This allows it to be used flexibly in variable production environments, particularly in areas with a high variety of product variants and low production volumes (high mix, low volume).

In this subproject, Aalen University of Applied Sciences is developing an LLM-supported interface that translates natural language directly into ROS2-compatible Python code for collaborative robots. This allows users to control robots via simple voice commands, without any programming knowledge. The system is being implemented as part of the AiHub framework, which combines LLMs with Retrieval-Augmented Generation (RAG). This allows domain-specific knowledge from technical documentation or safety-related specifications to be incorporated into the code generation. The resulting control commands are correct, context-sensitive, and safe.

The VISTA project is developing new approaches for managing manufacturing knowledge in increasingly complex production environments. The focus is on Vision-Language Models (VLMs), which combine image and text information to support assembly and maintenance workers with context-aware, cognitive assistance. This makes decisions faster, safer, and more informed. By intelligently linking visual data, machine signals, and language, VISTA enhances human-machine interaction, increases flexibility and safety, and makes expert knowledge more accessible—in line with the vision of a human-centered Industry 5.0.

Completed Projects

The 5G++ FlexiCell project has been funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK) since 2022 and concluded in March 2025. It aimed to deploy the 5G mobile communications standard as a campus network in manufacturing to reduce production costs. The digital transformation within the framework of Industry 4.0 poses a major challenge, particularly for small and medium-sized enterprises (SMEs). FlexiCell addressed this issue by developing solutions that reduce setup times in “high-mix, low-volume” (HMLV) production environments through intelligent networking and location technologies.

The AI Cockpit project, funded by the Federal Ministry of Labor and Social Affairs, focuses on the central questions of “Human in Command” and “Meaningful Human Control.” The aim is to explore how AI systems can be developed in which humans and machines collaborate efficiently and understand one another. In this context, a physical “AI Cockpit” is to be created that provides users with a transparent overview of the system’s decisions while also giving them the opportunity to actively influence them. This helps reduce the social risks associated with the technology’s impact and increases acceptance of such applications.

The Carl Zeiss Foundation has been supporting junior and endowed professorships through various programs for many years. The researchers receiving funding play a special role in the academic system, as their expertise enables them to provide new impetus and drive innovative developments. However, the financial resources needed to implement such projects quickly and effectively are often lacking. With the Prisma program, the foundation offers an unbureaucratic solution to provide targeted support to professors. The program is deliberately broad in scope and supports not only research and teaching but also initiatives that facilitate the transfer of scientific findings to industry or contribute to communicating science and research to society.

Aalen University of Applied Sciences’ AI Workshop for Small and Medium-Sized Enterprises page

Technology in Everyday Life

Machine learning is being used more and more in industry. AI and machine learning affect not only production workers but also managers. Humans and machines working hand in hand, with the machine providing support and humans having the final say—that is the ideal scenario we’re striving for, one that’s already a reality in fields such as aviation. Previous discussions about the degree of automation were successful and serve as the foundation for current research, such as that on autonomous driving.

Team

Prof. Dr. Doris Aschenbrenner

Room270

Anja Thomas

Antonia Uhle

News

University

FlexiCell project at Aalen University of Applied Sciences successfully completed

Sustainability

Werner T., Dawoud M., Aschenbrenner D. Cost-Efficient Detection of Plastics From Post-Consumer Packaging Waste Using Selected Bands in the Near-Infrared Spectrum. Macromolecular Materials and Engineering 2025. 10.1002/mame.202500143

Basedow N., Fangerow N., Hadasch K., Colloseus C., Aschenbrenner D. Using AI to Improve Post-consumer Plastics Recycling for Sustainability in a Smart Environment. In: Khalifa, N.E.M., Taha, M.N. (eds) Empowering AI Applications in Smart Life and Environment 2025. Springer, Cham.

Basedow N., Hadasch K., Dawoud M., Colloseus C., Taha I., Aschenbrenner D.: Open Data Sources for Post-Consumer Plastic Sorting: What We Have and What We Still Need. Procedia CIRP, Volume 122, 2024, pp. 1042–1047.

Fangerow N., Aschenbrenner D., Colloseus C., Khoury R.: Robot-assisted automated sorting techniques for plastic recycling. Procedia CIRP, Volume 120, 2023, pp. 1232–1237, ISSN 2212-8271.

Werner T., Taha I., Aschenbrenner D.: An overview of polymer identification techniques in recycling plants with a focus on current and future challenges. Procedia CIRP, Volume 120, 2023, pp. 1381–1386, ISSN 2212-8271.

Aschenbrenner, D., Gros, J., Fangerow, N., Werner, T., Colloseus, C., Taha, I.: Recyclebot – using robots for sustainable plastic recycling. Procedia CIRP, Volume 116, 2023, pp. 275–280, ISSN 2212–8271.

Industry 4.0

Feldmann, S., Schwarzer, S., Merkel, M., Saadati, H.R., Lenz, L., Gros, J., Kiener, C., Arulalan, A., Wiedenmann, M., Aschenbrenner, D.: Hybrid intelligence for collaborative assembly: Integrating human and robotic agents via shared perception–cognition–action cycles. In Proceedings of the 2025 International Conference on Sustainable Technologies for Humanity and Smart World (HSWTech) (pp. 1–6). IEEE.

Aschenbrenner, D., Colloseus, C.: Human in Command in Manufacturing. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol. 689. Springer, Cham, pp. 559–572.

Alizai A., Mohammad M.R., Ludwig S., Aschenbrenner D.: Heterogeneous Communication Networks and Localization for Industry 4.0 Applications in Small and Medium-Sized Enterprises: A Systematic Literature Review. Procedia CIRP, Volume 120, 2023, pp. 308–313, ISSN 2212-8271.

Eber R., Kollmann D., Aschenbrenner D., Hentsch M., Schwarzer S., Stricker N.: IIoT visualization applications based on augmented reality—a practical approach for easy implementation. Procedia CIRP, Volume 120, 2023, Pages 964–967, ISSN 2212-8271.

Gros J., Zatyagov D., Papa M., Colloseus C., Ludwig S., Aschenbrenner D.: Unlocking the Benefits of Mobile Manipulators for Small and Medium-Sized Enterprises: A Comprehensive Study. Procedia CIRP, Volume 120, 2023, Pages 1339–1344, ISSN 2212-8271.

Ludwig S., Aschenbrenner D., Scharle M., Klessig H., Karrenbauer M., Wu H., Taghouti M., Lozano P., Schotten, H.D., Fitzek, F.H.P.: Reference Network and Localization Architecture for Smart Manufacturing Based on 5G. In: Valle, M., et al. Advances in System-Integrated Intelligence. SYSINT 2022. Lecture Notes in Networks and Systems, vol. 546, 2023. Springer, Cham, pp. 470–479.

Aschenbrenner, D., Scharle, M., Ludwig, S.:5G++ FlexiCell: 5G Location-Based Context-Aware Agile Manufacturing. *Procedia CIRP* 107 (2022) 1455–1460.

Artificial/Hybrid Intelligence

Aschenbrenner, D., Hübner, A., Tagalidou, N., Bui, M., Vukelić, M., Yilmaz, N., & Basedow, N. (August 2025). AI Cockpit: A Meaningful Human Control Interface for Mitigating AI Risks in Hybrid Intelligence Systems. In IFIP International Conference on Advances in Production Management Systems (pp. 225–239). Cham: Springer Nature Switzerland.

Dassel, K., Colloseus, C., Sell, A., Günther, C., Aschenbrenner, D., Klein, J., & Guagnin, D. (2025). AI in Nursing Care—Putting People First: Participatory Development of a Digital Assistance System to Reduce Workload in Inpatient Elderly Care (iit White Paper). Institute for Innovation and Technology.

Aschenbrenner, D., Guagnin, D., Hanel, J., Hübner, A., Tagalidou, N., Yilmaz, N., & Zarbock, M. (2025). Faster Assistance, Smarter Management: The AI Cockpit for Smart Cities (iit White Paper). Institute for Innovation and Technology.

Hanel, J., Jantzen, L., Weselmann, L., Guagnin, D., Kempen, R., Peters, R., Saleh, F., & Steininger, R. (2025). Successfully Using AI in Job Matching: Fair and Transparent Application Processes with Human Oversight (iit White Paper). Institute for Innovation and Technology.

Aschenbrenner, Doris; Bottel, Matthias; Colloseus, Cecilia; Guagnin, Daniel; Hubel, Nikolas; Jantzen, Lisa; Kempen, Regina; Peters, Robert; Saleh, Faten; Sell, Andrea (2025). An AI Cockpit for Employees. Understanding, Confidently Using, and Controlling Artificial Intelligence in the Workplace. Institute for Innovation and Technology (iit), pp. 1–24.

Aschenbrenner, D., Kempen, R., Guagnin, D., Jantzen, L., Sell, A., Colloseus, C., Saleh, F., & Peters, R. (2025). AI Cockpit—Human Final Decision-Making Implemented in Accordance with the EU AI Act. In The World of Work and AI 2030: Challenges and Strategies for the Future of Work.

Burchardt, A., Aschenbrenner, D.:Practical Guide: AI = All Together and Interdisciplinary. In : Knappertsbusch, I., Gondlach, K. (eds.) Work and AI 2023. Springer, Wiesbaden, pp. 11–19.

Fiebig, T., Aschenbrenner, D.: 13 Propositions on an Internet for a “Burning World.”TAURIN+BGI '22: Proceedings of the ACM SIGCOMM Joint Workshops on Technologies, Applications, and Uses of a Responsible Internet and Building a Greener Internet, 2022.

Aschenbrenner, D.: The Importance of Participatory Design for Applications with Artificial Intelligence. In : Greiner, R., Berger, D., Böck, M.: Analytics and Artificial Intelligence 2022.

Aldea A., Tinga A.M., van Zeumeren I.M., van Nes N., Aschenbrenner D.: Virtual Reality Tool for Human-Machine Interface Evaluation and Development (VRHEAD). Conference : 2022 IEEE Intelligent Vehicles Symposium (IV).

Aschenbrenner, D., Zimmerling, M., & Diener, K.: Human-Centered Innovation System—An Integrated Innovation System for Overcoming the Limits of Theory and Practice. In: Peters R., Dicks M., Altepost A., Aschenbrenner D., Burmester M., Carolus A., Diener K., Fetic L., Gerst D., Hermann I., Kramm B., Kurz C., Peissner M., Suchy O., Westhoven M., Wienrich C., Zimmerling M.: Working with Artificial Intelligence 2022, p. 14.

Aschenbrenner D., Kramm B., Hermann I.:Culture as a Tool and Testing Ground for a Constructive Societal Discourse on Technology. In: Peters R., Dicks M., Altepost A., Aschenbrenner D., Burmester M., Carolus A., Diener K., Fetic L., Gerst D., Hermann I., Kramm B., Kurz C., Peissner, M., Suchy, O., Westhoven, M., Wienrich, C., & Zimmerling, M.: Working with Artificial Intelligence 2022, p. 9.

Social Studies

Uhle, A., Colloseus, C., Lenz, L., & Aschenbrenner, D. (March 2025). Designing a Dynamic Skill Tree for Self-directed Learning in Master’s Programs: A Learning Factory Approach. In Conference on Learning Factories (pp. 78–85). Cham: Springer Nature Switzerland.

Sell, A., & Colloseus, C.: “AI Integration Acceptance in Elderly Care Institutions: A Step Toward a Smarter Life.” In: Khalifa, N.E.M., Taha, M.N. (eds.) Empowering AI Applications in Smart Life and Environment 2025. Springer, Cham.

Aschenbrenner D., Jantzen L., Colloseus C., Sell A., and Kempen R.: Research Interpretation of Article 14 of the EU AI Act: Human in Command in Manufacturing. In : Thürer M., Riedel R., von Cieminski G., Romero, D. (eds.): Advances in Production Management Systems; 43rd IFIP WG 5.7 International Conference, APMS 2024 Chemnitz, Germany, September 8–12, 2024 Proceedings, Part III.

Colloseus, C: Artificial Tricksters: Narrating AI in Relation to Age and Gender. In : Gender Forum, Vol. 22, No. 2 (2023): Gender, Age, and the New Media, pp. 15–37.

Colloseus, C., Sell, A., Uhle, A.: Intelligent Machines? Religious Education Today, Jan.–Feb. 2023, pp. 4–9.

Robotics

Rieder, J. S., Kollmann, D., El Khoury, R., & Aschenbrenner, D.: Computer Vision-Based Environmental Perception for a Collaborative Robot. In IFIP International Conference on Advances in Production Management Systems (pp. 559–573). Cham: Springer Nature Switzerland.

Martz, U. M., Colloseus, C., Reinisch, U., & Aschenbrenner, D.: How Can a Miniature Arduino or ESP32-Based Architecture Be Designed to Mimic Basic Factory Scenarios for Use as a Learning Tool. In Conference on Learning Factories (pp. 242–249). Cham: Springer Nature Switzerland.

Borges E.I.A., Rieder J.S.I., Aschenbrenner D., Scharff R.B.N.: Framework for Armature-Based 3D Shape Reconstruction of Sensorized Soft Robots in eXtended Reality. Frontiers in Robotics and AI 2022, 9, Article 810328.

Ergonomics

Yilmaz, N., El Khoury, R., Jantzen, L., Kempen, R., & Aschenbrenner, D.: Evaluating User-Centered Visualizations of Traffic Anomalies: A User Study. In IFIP International Conference on Advances in Production Management Systems (pp. 178–193). Cham: Springer Nature Switzerland.

Li M., Yao X., Aschenbrenner D., van Eijk D., Vink P.: Ergonomics 4.0: Human-Centered Procedure for Ergonomic Design Using Virtual Reality Prototyping. Volume 32, Issue S1, Supplement: INCOSE Human Systems Integration Conference, November 16–19, 2021, Virtual Event, Pages 195–211.

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