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Instructors: Dr. Annika Peters; Dr. Manfred Eppe
Event type:
Project
Displayed in timetable as:
PJ Cogn.Robot
Hours per week:
6
Credits:
9,0
Language of instruction:
German/English
Min. | Max. participants:
- | 15
Registration group: Anmeldegruppe Projekte
More information:
Dear Students, due to the coronavirus the project Cognitive Robotics will NOT be held on
campus; given room numbers are irrelevant. The times however are valid.
If you wish to participate in the project, which will be held via Zoom, please send an
email to Annika Peters: apeters@informatik.uni-hamburg.de
Comments/contents:
The foundations of human cognition are often an inspiration for algorithms in Artificial Intelligence and Robotics. At the same time, the interaction between robots and humans plays an increasingly important role in our society. This leads to interdisciplinary research and applications in the areas of computer vision, signal processing, machine learning with neural networks, as well as the evaluation and design of human-robot interaction.
The goal of this project is to investigate these aspects and to learn to know the cognitive principles of human-robot interaction. Herein, the participants of the projects will be given access to the Pepper robot, in order to realize realistic human-robot interaction scenarios. The scenarios will be drawn from the RoboCup@Home competition, where robotic key capabilities like face detection, language processing and navigation must be implemented and integrated in order to handle situations like taking drink orders at a cocktail party. Herein, students will have the opportunities to take first steps in with neural networks and other AI methods, and to apply them in the context of robotic key capabilities.
Learning objectives:
The project group will be separated according to the individual’s interest with focus on pair programming. This technique stimulates continuous communication and knowledge transfer between the project partners. As every group is part of a team, the students get to know important project soft skills like time management, teamwork, and project management. After successful completion of the project, the students gained competence in their project field and learned how to communicate their development steps to the group helping to solve a complex problem.
Didactic concept:
The first part contains introduction of the topic and presentation of techniques required throughout the project. Individual open questions like the scenarios to be realized will be discussed with the students. The practical part of the course will consist of a single large project, where students will subdivide into teams of 2 students to tackle individual project parts. A weekly team meeting led by a team leader from the student group will provide time and space for progress report and solution suggestions for current problems. After successful integration of the modules, the students will test the scenario and evaluate several interaction aspects like system response time, reliability, etc. The results will be documented in a project report and demonstrated in a final presentation.
Literature:
- Raul Rojas, Neural networks : a systematic introduction (Inf-Bib: A ROJ 36077)
- Daniel T. Kaplan, Simon D. Levy, Kenneth A. Lambert: Introduction to scientific computation and programming in Python (Inf-Bib: P KAP 52918)
- Python Einführung online: http://www.scipy-lectures.org/intro/
Additional literature will be made available during the course of the project.
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