The implementation and design of cognitive Robot-Systems is a challenging process. Scientists and Enginerings must overview the physics of robots & their environments, sensors & sensor data, perception, probabilistic state estimation, knowledge representation and reasoning, robot learning, task and motion control, and cognitive architectures. It takes just as much effort to consider these issues when designing robots as it does to teach the entirety of robotics. How can we establish and foster the capabilities to understand the interrelation of constituent system parts and how systems work over time and within the context of larger systems (System thinking); the decomposition, pattern recognition, abstraction, and algorithm design (Computational thinking); the intrinsic motivation and willingness to solve challenges of robotics (Motivation); strategies, processes and abstraction (Mathematical thinking); the ability to make reasoned decisions (Decision making); and the awareness on how technology impacts (Sustainability)?
In this workshop, we address this very challenge by systematizing a best practice from experienced teachers. How is it possible to integrate the needs of all stakeholders? What are the perspectives of Students, Educators & Researchers, as well as state of the art in cognitive robotics? All of these considerations should also include the demands of society on the subject of cognitive robotics.
Content of the workshop
- System thinking - understanding of interrelation of system's constituent parts and how systems work over time and within the context of larger systems. To achieve this, students must be enabled to develop an understanding of a system's structure, the dynamic behavior of a system, system at a different scale, and reduce the complexity of a system (cf [Ross D. Arnold \& Jon Wade, 2015]). Applied to robotics, a roboticist needs to develop an awareness of the purpose of a robotic system as well as an understanding of the characteristics of a robotic system. In short: A roboticist must overview the hardware system, the software components, as well as, the implications of a developing environment.
- Computational thinking - Decomposition, pattern recognition, abstraction, and algorithmic design.
Teaching cognitve robotics includes the capability to decompose a comples problem or task into easy to solvable or understandable subtasks. TODO: Cognitive Robotics special
Following the decomposition, subtasks are solved by identifying patterns. These solutions are based on experience and known problem solving processes.
Understanding these patterns allows it to foucs on the most relevant aspects of the problem. Unimportant aspects of the problem are omitted. The focus is on the relevant details. The initial problem is greatly simplified.
Finally the understanding of tasks, subtasks, patterns, and abstractions can be defined in rules or algorithms.
- Mathematical thinking - problem solving and strategies, modeling of processes and objects, abstraction of objects and processes (Kodde-Buitenhuis, 2015)
- Decision making - the ability to make reasoned decisions
- Technology impact awareness - the ability to understand and reflect the effect of the developed system (Sustainability competence)
- Active learning - the intrinsic motivation and willingness to solve challenges of robotics
|08:30 – 09:00||Opening Session – Jörn Syrbe|
|09:00 – 10:00||Session 2: Research-oriented Teaching – Michael Beetz|
|10:00 – 11:00||Coffee break|
|11:00 – 12:30||Session 3|
|12:30 – 13:30||Lunch|
|13:30 – 14:00||Session 4|
|14:00 – 15:00||Session 5|
|15:00 – 16:00||Coffee break|
|16:00 – 17:30||Session 6|
- Dr. Jörn Syrbe University of Bremen
- Petra Wenzl University of Bremen
- Prof. Dr. h.c. Michael Beetz University of Bremen
• Educators, Policy makers, Researchers
The workshop will be supported by the Collaborative Research Center "Everyday Activity Science and Engineering (EASE)," funded by the German Research Foundation (DFG) at the University of Bremen. The workshop supported by the infrastructure project "Integrated e-Learning for Cognitive Robotics (IntEL4CoRo)", funded by the German Federal Ministry of Education and Research (BMBF).