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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Intelligent control of a pair of actuating muscles is synthesized from a biological paradigm of controlling these muscles (agonistic and antagonist) as they work in conjunction to provide actuation to a system (exoskeleton for a human). An investigation of muscle dynamics in humans and other animals is first conducted. Using the analogies from living muscle action, a paradigm is described on how to control such a system from an energy perspective subject to the biological constraints induced via the muscle dynamics. A discussion on the use of pneumatic muscle technology to power an exoskeleton suit is then presented

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For stroke survivors, or those with debilitating conditions, loss of autonomy and independence is a major issue. To help with this problem, a device is being designed that aids the movements of the wrist and hand. The device will measure the surface EMG readings from the forearm, and accurately interpret these readings to determine the intention of the device wearer. An exoskeleton, extending from before the wrist to the finger tips, will subsequently move in a manner that assists the wearer during the action — for example turning on or off a water tap. It is envisaged that the device will be capable of assisting in rehabilitative exercises with the ultimate goal being to make the wearer independent of the device, rendering it redundant. There are several aspects to this currently under investigation. Results are presented here outlining initial investigations into the design of the exoskeleton, the system to drive the exoskeleton, and the system to measure the surface EMG readings.

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