Seminar Details
2017-11-14 (14:00) : Improving learning in robotics by exploiting the structure and geometry of the data: application to prosthetic hands
At Euler building (room A.002)
Organized by Mathematical Engineering
Speaker :
Noémie Jaquier (Ecole Polytechnique Fédérale de Lausanne)
Abstract :
In many sensing and control applications, data are represented in the form of multidimensional arrays with particular geometric properties such as symmetries. Considering the underlying structure and geometry of the data can be beneficial in many robotics applications. This is particularly important in the context of robot learning from demonstration, when a small set of demonstrations is available, i.e. when the robots are required to reproduce tasks with generalization to new situations.
I will present different regression techniques and their extension to models that can efficiently exploit the specific structure and geometry of the acquired datapoints. The approaches will be illustrated in the application of controlling a prosthetic hand using tactile and electromyography to predict hand movements.