Concepts and framework

Design and development of concepts and a framework that can model the representations, computational tasks, and computational processes required for autonomous control of robots, as well as their interaction. For this purpose, the CRAM cognitive robot architecture is chosen as a starting point, since it has already been used to perform complex everyday tasks such as setting and clearing tables. This ensures that the conceptual framework is sufficient to program cognitive robots. Furthermore, the concepts will be axiomatized as an ontology, making the concept definitions unambiguous and machine-interpretable, and enabling the construction of a knowledge base that students can use to have queries about robots, robot control systems, and robot experiments answered automatically. For a robot experiment modeled and represented in this framework, students can use the knowledge base to answer questions such as: What did the robot see and do? How did it do it? Why…? etc.

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Learning opportunities and materials

Based on the conceptual framework, coherent learning opportunities and materials will be developed. In addition, a conceptualization for robot control systems and simulation environments will be designed corresponding to the IntEL4CoRo concepts and framework. This will allow students to explore and understand robot control software and robot experiments according to the conceptual framework. Teaching/learning materials include video lectures, lecture notes, slides, interactive tutorials, and handouts for the learning content listed in Figure 1.

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Teaching system and experimentation environment

Design and development of advanced robot control systems for teaching purposes and photorealistic physics-based simulation environments in which students can experiment with the control systems. The provided control systems and simulation environments will allow to illustrate the concepts of cognitive robotics taught in the courses (and scripts) and to generate tasks on all topics. In addition to solving smaller programming tasks, the learning environment will also enable the completion of theses (bachelor’s and master’s level), team-based software development projects, and robotics competitions. It will be possible to ensure that the results of the work are relevant to practice by configuring the teaching system with software components that can run on real robots. Furthermore, interactive simulation scenarios are provided in which autonomous robots assist and cooperate with humans to provide discussion bases for ELSI aspects of AI and cognitive robotics.

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Design, development, testing and iterative improvement of the teaching concept

The teaching concept to be developed for the IntEL4CoRo learning environment aims at competence-oriented and learner-centered higher education based on the AVIVA model (Städeli et al 2013) and provides an optimal framework for the didactic conceptualization of immersive didactically high-quality, sustainable teaching.

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Design and development of the IntEL4CoRo learning environment

Design and development of the IntEL4CoRo learning environment, which organizes the learning opportunities into teaching materials and teaching system components, implements the IntEL4CoRo teaching concept and realizes it with the help of the IntEL4CoRo learning content and materials and the IntEL4CoRo teaching system and experimental environment.

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IntEL4CoRo for everyone

The goal is not only to enable students of the AI focus to use the innovative teaching content: The didactic planning and implementation will also include content that will be made available as OER via the General Studies area of the University of Bremen. In this way, the project not only pursues innovative specialized training, but also the promotion of basic knowledge on AI and robotics for all students and other interested parties. For learners, a central point of contact is created through which all teaching content on the topic of AI-based robotics can be accessed, and existing learning materials and concepts are recombined.

The improved learning conditions through IntEL4CoRo will make the University of Bremen more attractive for learners and thus further strengthen the excellence of the University of Bremen in the field of AI. Additional added value will come from the increased visibility of Bremen’s research and teaching, and acting as a catalyst for the further development of networks, both international and interdisciplinary.

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