Development of a lightweight and high strength underactuated lower limb robot exoskeleton for gait rehabilitation

Abstract

The field of robot-assisted physical rehabilitation and robotics technology for providing support to the elderly population is rapidly evolving. Lower limb robot aided rehabilitation and assistive technology have been a focus for the engineering community over the last three decades as several robotic lower limb exoskeletons have been proposed in the literature as well as some being commercially available. One of the most important aspects of developing exoskeletons is the selection of the appropriate material. Strength to weight ratio is the most important factor to be considered before selection of a manufacturing material. The material selection strongly influences the overall weight and performance of the exoskeleton robot. In addition to material selection the type of mechanism and the actuation strongly effect the overall weight of the lower limb robotic exoskeleton. Most of the lower limb exoskeleton provided in the literature use a parallel mechanism, are properly actuated and either use aluminium or steel as their manufacturing materials. All these factors significantly increase the weight of the lower limb robot exoskeleton and make the device heavy, bulky, and uncomfortable for the wearer. Furthermore, an increase in weight contributes to a decrease of energy efficiency, reduces the energy efficiency of the final product, and increase the running cost of the designed robot devices. This thesis explores the wide-ranging potential of lower limb robot exoskeletons in the context of physical rehabilitation. Implementation and testing of a lightweight and high strength material without effecting the reliability was the main research objective of the present work. In this research, a linkage based under-actuated mechanism was used for the development of a lightweight design. Structural and mechanical load analysis of the mechanism was performed by using an advanced approach of finite element analysis. Three materials, namely structural steel, aluminium, and carbon reinforced fibre were compared as the manufacturing materials of the modelled mechanism. After that, a weight estimation was carried out for all three materials and the material which exhibits the best response under mechanical load analysis was selected. From the weight comparison, the carbon reinforced fibre provided the least weight for the digital twin of a lower limb exoskeleton. After material selection, the next step was the topology optimisation to further decrease the mass of the designed prototype without effecting the mechanical performance. The optimisation was carried out by using a multi-mode single objective genetic algorithm (GA) and a reduction of 30 % in the weight of the designed prototype was obtained. The selected material, which is carbon fibre, is a type of polymer material that is highly anisotropic, meaning it shows different material behaviour in different orientations of applied force. The next stage of the research work was the material characterization of the manufacturing material, which was carried out both analytically and experimentally. For defining the optimal criteria for fiber orientation, Hashin’s Failure Criteria is considered, and experimental work is performed to determine the most suitable fibre orientation. The material monotonic tensile properties were experimentally determined by experimental work and used to select a suitable orientation to manufacture a physical prototype model of the lower limb robot exoskeleton. After that the manufacturing process was carried out which is divided into three main steps. The first step was the use of the suitable lightweight and high strength material, which was selected by weight comparison in the design stage. The second step was the use of a single actuator to actuate the whole mechanical system and the final step was the use fabrication method to get a strong and reliable structure. Shaping of the different exoskeleton parts was carried out by CNC milling and parts were assembled to build a robotic prototype. A DC motor was used to actuate the complete prototype, which includes hip, knee, and ankle joints. In the end, a reliability analysis was carried out by using a machine learning based approach. A machine learning framework was developed for time-dependent reliability analysis of the developed robot. A neural network algorithm was designed to estimate the time-dependent reliability of the joint displacement and the positions of the end-effector first. From the above methodology, a lightweight and high strength lower limb robot exoskeleton was just not only conceptualized but a significant work was done to get a physical model starting from the material selection and concluding with the fabrication of a physical prototype. The reliability analysis gives an overview of the mechanism safety as a function of joint displacement. The designed prototype of carbon reinforced fibre was four times lighter in weight as compared to steel and three times lighter than aluminium, which is expected to give the wearer a comfortable wearing experience and improves the overall physical rehabilitation experience for the patients.

Date of Award	2024
Original language	English
Supervisor	Roland Goecke (Supervisor) & Masoud MOHAMMADIAN (Supervisor)