The capability of visualising and touching models of new products or new environments is a key factor in the design to production process. Usually this requires the construction of a physical model of the environment but production of the model can be costly and time consuming. Use of CAD packages can assist with the visualisation process, but proprioceptive and tactile sensations are required to augment this and provide the opportunity to feel the object. This work shows design, construction and testing in a virtual world of a generic 18 DOF proprioceptive input and feedback exoskeleton to monitor the motions of the human arm from sternum/spine to wrist and feedback tactile sensation generated during contact within a virtual world. The design is light, comfortable, and easy to wear for long periods providing an almost complete, unhampered range of input options. The proprioceptive inputs are augmented by tactile feedback of contact pressure (8 sensation points) to the upper and lower arm segments and pressure, texture, slip, edges/ridges/corners and thermal parameters to the hand. The paper shows how the input/feedback exoskeleton can be used to explore CAD designs generated in a commercial package (AutoCad) and imparted directly into a virtual world (WorldToolKit) permitting testing of products/processes before production and thereby improving the design-production process through the enhanced used of concurrent engineering techniques

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This paper presents the design of a direct driven under-actuated portable hand exoskeleton for rehabilitation. The design of the proposed Hand EXOskeleton SYStem (HEXOSYS) was driven by multi-objective optimisation strategy and inspiration from the human hand. The optimisation algorithm resulted in the choice of optimum link lengths of the device. The optimisation criteria are based on dexterity, isotropy and exertion of perpendicular forces on the finger digits. Furthermore, a series of experiments on the human hand using appropriate sensory instrumentation guided the selection of actuators thereby resulting in a rehabilitation device which is compatible with the human hand force capabilities. The provision of force as well as position feedback gives quantitative feedback to the therapist and would imply a more efficient rehabilitation process. The first prototype of the device has been designed and realized.

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The power assist walking legs (PAWL) is an autonomous exoskeleton robot which is designed for assisting activities of daily life. In order to improve the dynamic response of the exoskeleton robot, a novel sensing information forecasting algorithm is proposed based on the time series analysis. The algorithm is built up with the autoregressive (AR) model, the recursive least square (RLS) method and the final prediction error (FPE) criterion. The method of RLS is used to make the on-line parameters estimation, and the FPE criterion is used to select the order of AR model. Because of the real-time requirement, the forecasting algorithm is designed to be used on-line and to make predictions of force sensor’s information to ensure the real-time quality of the whole system. According to requirements, the algorithm can be categorized into two types: one step forecasting method and multi-step forecasting method. Meanwhile, we make some correlative simulations and experiments, and the experiments demonstrate the sensing information forecasting algorithm can predict the value and the trend of the sensing signal, the results of simulations and experiments illustrate the validity and effectiveness of the algorithm.

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The wearable power assist leg (WPAL) has been developed with the goal of decreasing human inner force / increasing human strength during walking in daily life for special groups, such as the old and the disabled. This paper summarizes the mechanical design using Ergonomics and analyses the dynamic characteristic of the exoskeleton robot considering the friction impact of the joints. According to the model of human muscle-bone, a control strategy mainly based on the human-robot interaction force between the exoskeleton and human leg is proposed. The WPAL is expected to have significant effect on many applications during activities of daily life. Correlative experiment apparatus and results are also covered at last.

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Enhancing robotic^1,2 surface mobility systems are a fundamental Mars Exploration Program goal because many surface-investigation goals require traversing significant distances in widely varying terrain conditions. SILVRCLAW (Stowable, Inflatable, Large, Vectran, Rigidizable, Cold-resistant, Lightweight, All-terrain Wheel) is an inflatable, rigidizable wheel technology that enables compact robotic vehicles to be deployed with significant ground clearance. Such a vehicle could traverse aggressive rocky terrains with a resultant low obstacle density (less than one obstacle per ~100m), travel over chasms with >1m separation, and offer the mission operator the ability to navigate with orbital-imaging resolution (i.e. with Mars Reconnaissance Orbiter’s Highrise telescope). Because of its high intrinsic mobility, SILVRCLAW can negotiate substantial obstacles, thus allowing a robotic rover to climb over obstacles as opposed to driving around them. Such capability could dramatically increase terrain access and rover range for a given weight class. In previous work, we reported on the development and initial testing of a SILVRCLAW exoskeleton wheel shell for purposes of understanding mobility performance and wear in Mars-like simulants. In this work we discuss environmental testbed results of a new cleated SILVRCLAW exoskeleton shell and the current development of a prototype deployable SILVRCLAW.

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