Register now After registration you will be able to apply for this opportunity online.
This opportunity is not published. No applications will be accepted.
Control Algorithm Development for a Series Elastic Actuated Exoskeleton
Robot-assisted therapy of stroke patients is a promising approach to improve the therapy outcome and to tackle the challenges of demographic ageing. Using a novel 6 DoF exoskeleton prototype, we want to investigate/develop new control strategies for the next generation of these robots.
Keywords: control development; system identification; recursive estimation; model predictive control; MPC; non-linear control; human-robot interface; computer vision; state-machine; rehabilitation engineering; multi-body control; torque control
_**Background:**_
Stroke is a leading cause of adult disability. There are about 64.5 million stroke survivors worldwide living with different degrees of disability. During a stroke, a part of the brain gets damaged. This often leads to a complete or partial loss of the motor function of one hemisphere. With the plasticity of the brain it is possible that neighboring healthy parts of the brain learn the function of the damaged. Functional movement therapy aims to induce this plasticity by moving the patient’s arm or assisting the patient to move. Robot-assisted therapy has the potential to improve the therapy outcome and to solve emerging issues caused by demographic ageing. Exoskeleton robots offer the control over all joints of a limb which is needed for treatment of severely to mildly affected patients.
_**The Project:**_
With a newly developed series elastic actuated 6 DoF exoskeleton we want to investigate new control approaches to improve the quality of the physical human robot interaction and the efficiency of the therapy. How can we improve the haptic transparency of the robot (i.e. the user does not feel undesired interaction forces when moving in the device)? How can the robot determine the needed assistance for the patient in general movements in an efficient manner? How can the robot assess and express the human disability in order to improve the therapists understanding of the disability? How to control the redundant DoF to generate physiological movements with the robot? How can we improve the safety of these devices in autonomous operation? Modern control techniques and the precise torque controllability of the exoskeleton prototype offer the basis to develop solutions for these questions.
_**Your task:**_
In this project you will strive to find an answer to one of these research questions. Therefore, you will implement one or multiple control strategies, estimators, algorithms, and/or CV pipelines and test them in simulation and on the hardware.
_**Background:**_ Stroke is a leading cause of adult disability. There are about 64.5 million stroke survivors worldwide living with different degrees of disability. During a stroke, a part of the brain gets damaged. This often leads to a complete or partial loss of the motor function of one hemisphere. With the plasticity of the brain it is possible that neighboring healthy parts of the brain learn the function of the damaged. Functional movement therapy aims to induce this plasticity by moving the patient’s arm or assisting the patient to move. Robot-assisted therapy has the potential to improve the therapy outcome and to solve emerging issues caused by demographic ageing. Exoskeleton robots offer the control over all joints of a limb which is needed for treatment of severely to mildly affected patients.
_**The Project:**_ With a newly developed series elastic actuated 6 DoF exoskeleton we want to investigate new control approaches to improve the quality of the physical human robot interaction and the efficiency of the therapy. How can we improve the haptic transparency of the robot (i.e. the user does not feel undesired interaction forces when moving in the device)? How can the robot determine the needed assistance for the patient in general movements in an efficient manner? How can the robot assess and express the human disability in order to improve the therapists understanding of the disability? How to control the redundant DoF to generate physiological movements with the robot? How can we improve the safety of these devices in autonomous operation? Modern control techniques and the precise torque controllability of the exoskeleton prototype offer the basis to develop solutions for these questions.
_**Your task:**_ In this project you will strive to find an answer to one of these research questions. Therefore, you will implement one or multiple control strategies, estimators, algorithms, and/or CV pipelines and test them in simulation and on the hardware.
The work packages will be tailored to your interest and the current need in the project. Work packages could be composed of:
- literature research (short)
- system modeling
- development of controls(e.g. linear and nonlinear control, MPC, high-level policies), system estimation and/or computer vision pipelines
- theoretical proof of performance (e.g. robustness, stability)
- experiments on the hardware
The work packages will be tailored to your interest and the current need in the project. Work packages could be composed of:
- literature research (short) - system modeling - development of controls(e.g. linear and nonlinear control, MPC, high-level policies), system estimation and/or computer vision pipelines - theoretical proof of performance (e.g. robustness, stability) - experiments on the hardware
We are searching for motivated students with:
- good understanding of multi-body systems
- good understanding of control system theory
An advantage is:
- working experience in C++
- working experience with ROS
- knowledge of advanced control methods (e.g. lectures like Model Predictive Control, Recursive Estimation, Dynamic Programming and Optimal Control etc.)
We are searching for motivated students with:
- good understanding of multi-body systems - good understanding of control system theory
An advantage is:
- working experience in C++ - working experience with ROS - knowledge of advanced control methods (e.g. lectures like Model Predictive Control, Recursive Estimation, Dynamic Programming and Optimal Control etc.)
If you are interested in the project please apply with your CV, academic transcript, and a short description of your interest in the project to:
Yves Zimmermann (yvesz@ethz.ch)
If you are interested in the project please apply with your CV, academic transcript, and a short description of your interest in the project to: