Human-Robot Interaction, Summer Semester 2021
In this seminar, the current research studies on human-robot interaction (HRI) will be introduced. The course content involves both theoretical (such as embodiment, anthropomorphism, and emotions) and practical (e.g., HRI experiment design, robot types and sensors, and programming machine learning pipeline) aspects of human-robot interaction. We will particularly focus on interdisciplinary studies at the intersection of psychology, neuroscience, and robotics. Additionally, the Pepper humanoid and Nao robots will be available – depending on the Covid regulations in HU-Berlin– for designing and performing HRI experiments.
Web site: http://www.robotmultimodal.com/hri/
Moodle link: https://moodle.hu-berlin.de/course/view.php?id=104289
Machine learning in robotics, Winter Semester 2020/2021
In this seminar, current topics and methods of machine learning with application in robotics are discussed. In particular, we focus on new developments in deep learning applications – namely robot vision, cognitive-developmental tasks, and multimodal learning– in humanoid robotics. To pass this course, the students should develop machine learning models with robot datasets, propose team projects, presents results in oral presentations and written reports.
Web site: http://www.robotmultimodal.com/mlr/
Moodle link: https://moodle.hu-berlin.de/enrol/index.php?id=100124
Multimodal machine learning, Summer Semester 2020
This seminar introduces the foundations of multimodal machine learning and applications on simulated and actual robot platforms. It covers the basics of machine learning, preliminary concepts of sensors (e.g., depth and color cameras, IMU, position encoders, etc.), multimodal sensor fusion techniques, specifications of robot platforms (e.g., Nao and the Pepper), and simulators. Students will work in teams on a topic in (deep) multimodal learning for robotics and present their experimental results in oral presentations and written reports.
Web site: http://www.robotmultimodal.com/mml/
Moodle link: https://moodle.hu-berlin.de/enrol/index.php?id=94968