Currently, wearers of full body exoskeletons are hindered in their ability to use their upper body as desired due to the rigid back parts used in these devices. In order to maximize their versatility the design and preliminary testing is shown of an exoskeletal spine mechanism, called “exo-spine”, that allows the wearer to move all degrees of freedom of his spine and shoulder girdle. Based on the primary forces to be supported during lifting, identified as gravity forces from loads lifted in front of the wearer, as well as functional degrees of freedom, which is a control strategy used by our central nervous system, this mechanism can be actuated using only one motor to provide the required support. Experiments indicate a substantial, although not problematic amount of friction as well as further requirements for the control of the assisting force. Besides improving exoskeletons its basic structure and design principles may be successfully applied to rehabilitation as well.

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Coupling the human upper limbs with robotic devices is gaining increasing attention in the last decade, due to the emerging applications in orthotics, prosthetics and rehabilitation devices. In the cases of every-day life tasks, force exertion and generally interaction with the environment is absolutely critical. Therefore, the decoding of the user’s force exertion intention is important for the robust control of orthotic robots (e.g. arm exoskeletons). In this paper, the human arm manipulability is analyzed and its effect on the recruitment of the musculo-skeletal system is explored. It was found that the recruitment and activation of muscles is strongly affected by arm manipulability. Based on this finding, a decoding method is built in order to estimate force exerted in the three-dimensional (3D) task space from surface ElectroMyoGraphic (EMG) signals, recorded from muscles of the arm. The method is using the manipulability information for the given force task. Experimental results were verified in various arm configurations with two subjects.

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This paper presents a bio-inspired below-knee exoskeleton to assist human walking. Different from the passive orthotic devices, the proposed exoskeleton includes powered compliant ankle and toe joints, which can output sufficient power to help the one withexoskeleton relearn normal walking gaits. We first propose a passivity-based dynamic bipedal model to analyze the effects of segmented foot and compliant joints on energetic efficiency and stability of bipedal walking. Starting from the results of theoretical analysis, we construct a below-knee exoskeleton prototype with ankle and toe joints driven by two series-elastic actuators. Experimental results validate the effectiveness of the proposed exoskeleton.

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The PERCRO laboratory of Scuola Superiore Sant’Anna has recently completed the development and functional assessment of the Body Extender (BE) system, an advanced wearable robot expressly conceived for augmenting the human strength for handling of heavy materials in unstructured environment. The system is composed by four robotic limbs with anthropomorphic kinematics and has a total of 22 independently actuated degrees of freedom. The leg locomotion and the force servo-amplification allow operations in environments that are hardly accessible by the conventional handling systems preserving the force sensibility during the manipulative tasks. Possible applications are handling of military materials in narrow spaces, rescuing of victims in natural and human provoked disasters and handling of heavy parts in the manufacturing of large products. The paper reports the system specifications taken as a reference for the design, the criteria and verification methods, the architectural solutions used for the implementation of mechanics, electronic and control components and the results of the preliminary experimental assessment.

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Recognizing the user motion intention plays an important role in the study of power-assist robots. An intention-guided control strategy is proposed for the upper-limb power-assist exoskeleton. A force sensor system comprised of force sensing resistors (FSRs) is designed to online estimate the motion intention of user upper limb. A new concept called “intentional reaching direction (IRD)” is proposed to quantitatively describe this intention. Both the state model and the observation model of IRD are obtained by enumerating the upper limb behavior modes and analyzing the relationship between the measured force signals and the motion intention. Based on these two models, the IRD can be online inferred by applying filtering technology. Guided by the estimated IRD, an admittance control strategy is assumed to control the motions of three DC motors in the joints of the robotic arm. The effectiveness of the proposed approaches is finally confirmed by the experiments on a 3-DOF robotic exoskeleton.

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