This paper investigates the key factors associated with the realization of a hand exoskeleton to be embedded in an astronaut’s EVA glove, in order to overcome the stiffness of the pressurized space suit. An overview is provided, laying the ground for the forthcoming prototype study, design and construction, by presenting the main constraints related to the realization of a hand exoskeleton for EVA suits and a preliminary concept analysis of possible solutions in terms of mechanical structure, actuators and sensors. The future exoskeleton will be a complex mechatronic system detecting the operator’s movement through sensors, processing the acquired data and generating the motion through its actuation system.

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The increased interest in wearable robots for rehabi-litation and human assistance has also increased demands for lightweight and elastic actuators with inhe-rent compliance for safe human-robot interactions. Although braided type McKibben actuators are frequently used as artificial muscles for robotic applications, they have two drawbacks. First, the weight and size of the necessary compressor and control valves limit the applications of these actuators as autonomous robots. Second, the control accuracy of these actuators is decreased by long tube connections that often cause pressure oscillations. This paper describes a pressure tracking controlled servo drive, using a McKibben actuator and miniaturized unconstrained on off valves, which are smaller in size and easier to implement. The properties of unconstrained on-off valves are discussed, and different pressure control algorithms are compared. The pressure tracking control was also tested experimentally for its ability to track irregular waveforms at various pressure levels.

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The design of a robotic exoskeleton often focuses on replicating the kinematics of the human limb that it is connected to. However, human joint kinematics is so complex that in practice, the kinematics of artificial exoskeletons fails to reproduce it exactly. This discrepancy results in hyperstaticity. Namely, uncontrolled interaction forces appear. In this paper, we investigate the problem of connecting an exoskeleton to a human member while avoiding hyperstaticity; to do so, we propose to add passive mechanisms at each connection point. First, analyzing the twist spaces generated by these fixation passive mechanisms, we provide necessary and sufficient conditions for a given global isostaticity condition to be respected. Then, we derive conditions on the number of Degrees of Freedom (DoFs) to be freed at the different fixations, under full kinematic rank assumption. We finally apply the general methodology to the particular case of a 4 DoF shoulder-elbow exoskeleton. Experimental results allow to show an improvement in transparency brought by the passive mechanism fixations.

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Previous studies from our laboratory have demonstrated that the choice of control algorithm greatly affects how a human adapts to a robotic lower limb exoskeleton. We have shown that proportional myoelectric controllers have distinct advantages over kinematic based controllers in healthy humans. However, many neurologically impaired patients that could benefit from a robotic lower limb exoskeleton do not have sufficient muscle activation patterns for robust myoelectric control. Our long term goal is to develop an artificial neural oscillator that can provide adaptive control for robotic lower limb exoskeletons and other robotic assistive devices for human locomotion. As a first step towards this goal, we used computer simulations to assess the stability and robustness of various neural oscilla-tor algorithms coupled with dynamic systems. Due to the pendular nature of human walking mechanics, our dynamic systems included damped pendulums and a three-dimensional passive dynamic walker. We used a Hopf oscillator as our artificial neural oscillator providing neural control to the actuators. Overall results indicated that the Hopf oscillator could entrain to the resonant movement dynamics of the mechanical system with sufficient proprioceptive feedback. Our future work will examine methods to shape the timing and profile of the Hopf oscillator output to more closely mimic human muscle activation patterns. After coupling the revised Hopf oscillator to more complex dynamic walking models, we plan on testing their implementation on the robotic lower limb exoskeletons in our laboratory.

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The availability of accurate and comprehensive models of human limbs, combining high reliability and real-time operation, is required to develop seamless and intuitive human-machine interfaces. Biomechanist have developed complex models of the human lower limb, combining kinematics and kinetics data with neural signals for the purpose of studying human motor control strate-gies. The complexity prevent their application to situations with stringent real-time requirements. We are currently working on the enhancement of an EMG-driven model of the human lower extremity to achieve compre-hensiveness, accuracy, and fast runtime execution. Starting from the very complex model developed by Lloyd et al. we have evaluated how this model can be enhanced to achieve higher performances in terms of compu-tation time with no loss of prediction accuracy. The enhanced model will be applied to the control of powered orthosis and to the development of advanced biomimetic control systems for humanoids robots. We started our investigation with the analysis of the impact of modeling the tendon as an infinitely stiff body and quantitatively evaluated the changes in the behavior of the modified model w.r.t. the original one. We also integrated a runtime anatomical model that allowed to execute the whole EMG-driven model at runtime. This is a significant improvement as the previous available model could not entirely be executed at runtime due to the complexity of the original anatomical model.

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