Algorithms and strategies to properly solve the inverse kinematics of a 7 Degrees of Freedom Rehabilitative Exoskeleton
Thesis in external company
External reference persons Giulia Bodo (IIT-Genova)
Research Groups 17 - Progettazione di macchine rotanti e sistemi meccatronici
Thesis type MODELING, NUMERICAL AND EXPERIMENTAL
Description Humans are probably one of the best examples of redundant systems, as humans we have the possibility to move our limbs and locate them inside the space with an immediate correlation between what we want to reach and how to configure our body to achieve that goal. But how to translate this intrinsic human logic into a mathematical algorithm? Inverse kinematics allows to establish the required relations between where the end-effector should go and how to move the joints to reach that target. Inverse kinematics (IK) study is fundamental to control a robotic device, more and more if it works at strict contact with a human, several methods have been studied and proposed in literature, but in the context of rehabilitative robotics there is still a lack of strategies that allow a physiologically acceptable computation of the inverse kinematics.
The candidate will face the challenge to explore and implement novel algorithms and strategies to properly solve the inverse kinematics of a 7 Degrees of Freedom Rehabilitative Exoskeleton to obtain an IK solution that meets the physiological requirements. The candidate will focus both on the biomechanics and the robotic workspace evaluation for the shoulder complex.
Additionally, there will be the opportunity to explore ground-breaking control strategies, including the implementation of a hybrid assistive control system that combines impedance control with Functional Electrical Stimulation (FES).
See also thesisproposal_2.pdf
Required skills The ideal candidate has a mechatronic background, with a good knowledge of robotics and good skills in using the Matlab/Simulink environment.
Deadline 28/02/2024 PROPONI LA TUA CANDIDATURA