An Empirical Analysis of Methods for Learning Robot Kinematics from Demonstration

In this work, we compare two different approaches, namely Koopman Operators and Neural Networks to learning robot kinematics from demonstration data:

Project partner: Alexander Broad

Responsibilities: Implementation of the neural network learning.

mwrw_2017_2