5 research outputs found

    Machine-Knitted Seamless Pneumatic Actuators for Soft Robotics: Design, Fabrication, and Characterization

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    Computerized machine knitting offers an attractive fabrication technology for incorporating wearable assistive devices into garments. In this work, we utilized, for the first time, whole-garment knitting techniques to manufacture a seamless fully knitted pneumatic bending actuator, which represents an advancement to existing cut-and-sew manufacturing techniques. Various machine knitting parameters were investigated to create anisotropic actuator structures, which exhibited a range of bending and extension motions when pressurized with air. The functionality of the actuator was demonstrated through integration into an assistive glove for hand grip action. The achieved curvature range when pressurizing the actuators up to 150 kPa was sufficient to grasp objects down to 3 cm in diameter and up to 125 g in weight. This manufacturing technique is rapid and scalable, paving the way for mass-production of customizable soft robotics wearables

    Soft Gloves: A Review on Recent Developments in Actuation, Sensing, Control and Applications

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    Interest in soft gloves, both robotic and haptic, has enormously grown over the past decade, due to their inherent compliance, which makes them particularly suitable for direct interaction with the human hand. Robotic soft gloves have been developed for hand rehabilitation, for ADLs assistance, or sometimes for both. Haptic soft gloves may be applied in virtual reality (VR) applications or to give sensory feedback in combination with prostheses or to control robots. This paper presents an updated review of the state of the art of soft gloves, with a particular focus on actuation, sensing, and control, combined with a detailed analysis of the devices according to their application field. The review is organized on two levels: a prospective review allows the highlighting of the main trends in soft gloves development and applications, and an analytical review performs an in-depth analysis of the technical solutions developed and implemented in the revised scientific research. Additional minor evaluations integrate the analysis, such as a synthetic investigation of the main results in the clinical studies and trials referred in literature which involve soft gloves

    Data-driven Mechanical Design and Control Method of Dexterous Upper-Limb Prosthesis

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    With an increasing number of people, 320,000 per year, suffering from impaired upper limb function due to various medical conditions like stroke and blunt trauma, the demand for highly functional upper limb prostheses is increasing; however, the rates of rejection of prostheses are high due to factors such as lack of functionality, high cost, weight, and lack of sensory feedback. Modern robotics has led to the development of more affordable and dexterous upper limb prostheses with mostly anthropomorphic designs. However, due to the highly sophisticated ergonomics of anthropomorphic hands, most are economically prohibitive and suffer from control complexity due to increased cognitive load on the user. Thus, this thesis work aims to design a prosthesis that relies on the emulation of the kinematics and contact forces involved in grasping tasks with healthy human hands rather than on biomimicry for reduction of mechanical complexity and utilization of technologically advanced engineering components. This is accomplished by 1) experimentally characterizing human grasp kinematics and kinetics as a basis for data-driven prosthesis design. Using the grasp data, steps are taken to 2) develop a data-driven design and control method of an upper limb prosthesis that shares the kinematics and kinetics required for healthy human grasps without taking the anthropomorphic design. This thesis demonstrates an approach to decrease the gap between the functionality of the human hand and robotic upper limb prostheses by introducing a method to optimize the design and control method of an upper limb prosthesis. This is accomplished by first, collecting grasp data from human subjects with a motion and force capture glove. The collected data are used to minimize control complexity by reducing the dimensionality of the device while fulfilling the kinematic and kinetic requirements of daily grasping tasks. Using these techniques, a task-oriented upper limb prosthesis is prototyped and tested in simulation and physical environment.Ph.D
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