This article presents the kinematic analysis and implementation of an interface and control of two robots-an exoskeleton master robot and a human-like slave robot with two arms. Two robots are designed and built to be used for motion-following tasks. The operator wears the exoskeleton master robot to generate motions, and the slave robot is required to follow after the motion of the master robot. To synchronize the motions of two robots, kinematic analysis is performed to correct the kinematic mismatch between two robots. Hardware implementation of interface and control is done to test motion-following tasks. Experiments are performed to confirm the feasibility of the motion-following tasks by two robots.

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This paper gives an overview of different robotic applications based on two compliant actuator technologies developed within the Robotics & Multibody Mechanics Research Group at Vrije Universiteit Brussel: the Pleated Pneumatic Artificial Muscle (PPAM) and the Mechanically Adaptable Compliance and Controllable Equilibrium Position Actuator (MACCEPA). Both actuators have built-in intrin-sic compliance, which makes for two control parameters to be set, namely the equilibrium position of the actuated joint and the equivalent torsion spring stiffness. The increase of control complexity is countered by the added value of adaptable compliance. Compliant actuation, as opposed to conventional, stiff actuators like electrical drives, is currently growing in importance and has applications in a variety of robotic technologies where accurate trajectory tracking is not prevalent: bipedal walking robots, assistive technology, rehabilitation training. The current status of our research projects in compliant actuation and their future perspectives are presented.

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Our previous results indicated that when bilateral ankle exoskeletons produce ~65% of ankle joint power, the metabolic cost of level walking decreased by 13% (Sawicki et al., 2007). Because level, steady speed walking requires no net mechanical work over a stride, substituting biological muscle work with artificial muscle work may yield larger reductions in energy expenditure during locomotor tasks that require substantial positive muscle work. The objective of this study was to determine the effects of increasing surface incline on the metabolic cost of walking with robotic exoskeletons. We hypothesized that as surface gradient increased, ankle exoskeletons would deliver more mechanical power and users would save more metabolic energy.

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The development of innovative exoskeletons for the upper limb requires a strong collaboration between robotics and neuroscience. The robotic system will be deeply coupled to the human user and the exoskeleton design should be based on the human model in terms of biomechanics, and control and learning strategies. This paper presents the results of the design process of the NEUROExos exoskeleton. The catching of a moving object has been chosen as reference task from a neuroscience point of view and an ad-hoc setup has been designed and realized. Experiments has been per-formed and the obtained results has been used to design and develop a bioinspired two joints-two links ro-botic arm: the NEURArm platform. It has been developed for implementing bioinspired control strategies and for obtaining a human-like robotic arm to be used for assessing active exoskeletons in fully safe condi-tions. The main features of the NEUROExos elbow module platform and the on going activities related to human/machine interface are presented.

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Using CMU actuators, a Prototype of Mechanical Assis-tance Device for the Wrist’s Flexion Movement (PMA) was developed and probed in a mechanical model, in or-der to be implemented in a future as a dynamic powered orthosis or as a rehabilitation assistant instru-ment. Two Mayor Actuators conformed by three CMU actuators arranged in a series configuration, allows to an artificial hand to be placed in four predefined positions: 0º, 20º, 40º and 60º. The synchronism and control of the actuators is achieved with the Programmable Control Module (PCM). It is capable to drive up to six CMU actuators, and possess two different modes of execution: a Manual mode and an Exercise mode. In the Manual Mode, the position of the hand responds directly to the commands of the keyboard of the front panel, and in the Exercise mode, the hand realizes a repetitive and programmed movement. The prototype was tested in 100 positions in the Manual Mode and for 225 works cycles in the Exercise Mode. The relative re-petition error was less than 5% for both test. This prototype only consumes 4,15W, which makes it possible to be powered by small rechargeable batteries, allowing its use as a portable device.

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