Rehabilitation devices, such as powered wheelchairs, assistive robotic arms, and limb prostheses, offer significant assistance to individuals with residual motion capabilities due to conditions such as stroke, disease, amyotrophic lateral sclerosis (ALS), amputations, and spinal cord or brain injuries. The interfaces used to control these devices (e.g., joysticks, head arrays, sip-and-puff systems, and electromyography sensors) limit their effectiveness in controlling robotic devices with a high number of degrees of freedom (DoFs) as the amount of human signals decreases. Previous studies have explored the use of compensatory motions performed by prosthetic users to control upper-limb prostheses with up to 2-DoFs. Building upon this concept, I have introduced a novel methodology that is generalizable to multiple robotic systems with a high and variable number of DoFs. Within this framework, it becomes feasible to control several assistive robotic devices based on the residual movements unique to each individual with reduced mobility. I employed inertia measurements unit (IMU) sensors to read the motions performed by the user, intended to reach an object, and used these signals to generate prosthetic joint commands according to the user’s intentions. The robotic joints are then responsible for reaching the object. This thesis presents the proposed control algorithm, describing its initial formulation and development into a more general and valid law. I validated the algorithm through simulations and experiments, starting from a prosthetic case and further expanding this algorithm for the control of an avatar, such as the two-wheeled robot Alter-Ego. These experiments with an avatar robot inspired me to conceptualize the robot as a sort of “whole-body prosthesis”, wherein the assistive device is perceived as an artificial extension of the user’s body. Consequently, I have further intensified my research on exploring the applicability of this framework for assistive purposes, both in domestic and clinical settings, with individuals experiencing reduced mobility, such as those with spinal cord injuries or amyotrophic lateral sclerosis (ALS). Through these studies, a generalized method is investigated that enables the control of multi-DoFs robotic devices for assistance and rehabilitation purposes. This opens the door to a generalization of the human-robotic device dynamic system, which can be applied in fields beyond rehabilitation.
Generalized compensatory Control for Human-Robot Integration: Applications to Multi-Dof Prostheses and Avatars
FEDER, MADDALENA
2025
Abstract
Rehabilitation devices, such as powered wheelchairs, assistive robotic arms, and limb prostheses, offer significant assistance to individuals with residual motion capabilities due to conditions such as stroke, disease, amyotrophic lateral sclerosis (ALS), amputations, and spinal cord or brain injuries. The interfaces used to control these devices (e.g., joysticks, head arrays, sip-and-puff systems, and electromyography sensors) limit their effectiveness in controlling robotic devices with a high number of degrees of freedom (DoFs) as the amount of human signals decreases. Previous studies have explored the use of compensatory motions performed by prosthetic users to control upper-limb prostheses with up to 2-DoFs. Building upon this concept, I have introduced a novel methodology that is generalizable to multiple robotic systems with a high and variable number of DoFs. Within this framework, it becomes feasible to control several assistive robotic devices based on the residual movements unique to each individual with reduced mobility. I employed inertia measurements unit (IMU) sensors to read the motions performed by the user, intended to reach an object, and used these signals to generate prosthetic joint commands according to the user’s intentions. The robotic joints are then responsible for reaching the object. This thesis presents the proposed control algorithm, describing its initial formulation and development into a more general and valid law. I validated the algorithm through simulations and experiments, starting from a prosthetic case and further expanding this algorithm for the control of an avatar, such as the two-wheeled robot Alter-Ego. These experiments with an avatar robot inspired me to conceptualize the robot as a sort of “whole-body prosthesis”, wherein the assistive device is perceived as an artificial extension of the user’s body. Consequently, I have further intensified my research on exploring the applicability of this framework for assistive purposes, both in domestic and clinical settings, with individuals experiencing reduced mobility, such as those with spinal cord injuries or amyotrophic lateral sclerosis (ALS). Through these studies, a generalized method is investigated that enables the control of multi-DoFs robotic devices for assistance and rehabilitation purposes. This opens the door to a generalization of the human-robotic device dynamic system, which can be applied in fields beyond rehabilitation.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/215712
URN:NBN:IT:UNIPI-215712