Lecturer: Tim Tiedemann
Fields: Robotics, Machine Learning
Content
This course will show a bridge between machine learning and robotics — which does not use ML to solve robotics’ tasks but the other way around! Further, the course tries to show where using robots could be a method to help finding biological or cognitive psychological insights.
– Session 1 will give an introduction first to bio-robotics, and afterwards to robotics in general — including robotic software frameworks and potential starting points for own robotic experiments. Here, examples are shown where biology gained new insights from robotics (and the other way around, too).
– Session 2 will continue the introduction to robotics and starts the introduction to active learning with methods that are NOT active learning (but that could help solving problems you have with large data sets you need to label…).
– Session 3 will continue on active learning and combine both, robotics and active learning. We will also talk about the idea of embodiment, here.
Literature
- Siciliano et al. (Eds.) (2016, 2024): Handbook of Robotics. Springer
- Burr Settles: Active Learning, Morgan & Claypool Publishers, 2012
- Robert (Munro) Monarch: Human-in-the-Loop Machine Learning : Active Learning and Annotation for Human-Centered AI, Shelter Island, NY: Manning, 2021
Lecturer
Since 2016: Professor of Intelligent Sensing at the University of Applied Sciences Hamburg (HAW Hamburg, Hamburg, Germany). Main research interests are sensors and sensor data processing (including machine learning methods) and robotics. 2010-2016 Postdoc in the area of space and underwater robotics at the German Research Center for Artificial Intelligence (DFKI) in Bremen, Germany. 2009 Ph.D. in biorobotics, focus on the transfer of (neuro-) biological concepts to the robotic domain 2003-2010 Research assistant at the Computer Engineering Group, Bielefeld University 2003 Research assistant at the Cognitive Psychology Group, Bielefeld University 2003 Diploma in computer science (i.e. Master degree level), study computer science with a focus on robotics and neural networks at Bielefeld University, Bielefeld, Germany
Affiliation: HAW Hamburg