This lab aims at, in a first part, introducing the inverse kinematics of Emio using a multilayer perceptron (MLP) to model the mapping from end-effector position to motor angles. In a second part, the concept of parametric model is introduced to calibrate the youg modulus.
Knowledge Requirements:
- Programming with PyTorch
- Understanding of forward kinematics
- Undergraduate level for numerical methods
This lab was made by Assistant Pr. Frederike Dumbgen in collaboration with Compliance Robotics. You can find the original repo here.