This paper studies the integration of a human arm with a powered exoskeleton (orthotic device) and its experimental implementation in an elbow joint, naturally controlled by the human. The human-machine interface was set at the neuromuscular level, by using the neuromuscular signal (EMG) as the primary command signal for the exoskeleton system. The EMG signal along with the joint kinematics were fed into a myoprocessor which in turn predicted the muscle moments on the elbow joint. The moment-based control system integrated myoprocessor moment prediction with feedback moments measured at the human arm/exoskeleton and external load/exoskeleton interfaces. The exoskeleton structure under study was a two-link, two-joint mechanism, corresponding to the arm limbs and joints, which was mechanically linked by the human operator. Four indices of performance were used to define the quality of the human/machine integration and to evaluate the operational envelope of the system. Experimental results indicate the feasibility of an EMG-based power exoskeleton system as an integrated human-machine system using high-level neurological signals.

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The development of haptic systems for VR and telepresence has been identified as a key feature in the progression from observation of the environment to interaction. Arm masters and exoskeletons have formed an important user interface for the provision of such facilities, with these devices requiring a subtle combination of complex mechanical, electrical and kinematic structures with user requirements of low mass, portability, comfort, flexibility and safety. The actuation system is often identified as a focus of this design blending process. This work considers the design, construction and testing of a light weight comfortable high power 7 degree of freedom force feedback exoskeleton. This is achieved through the use, modeling and control of pneumatic muscle actuators (pMA) that provide lightweight, low cost, flexible, portable, comfortable and inherently safe input/feedback/control operation. Models of operation in a virtual environment are developed and demonstrated, with experimental results to illustrate the effectiveness of the device in replicating contact forces and creating a sensation of virtual presence.

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This paper analyzes the general requirements of Haptic Interfaces (HIs) for Virtual Prototyping operations. In particular two different paradigms of interaction with virtual objects are presented, respectively based on an anthropomorphic and a desktop Haptic Interface. The main aspects of mechanical and control system design of HIs and force rendering in Virtual Environments are discussed too. The experimental results of the simulations conducted with a force feedback arm exoskeleton are presented, pointing out the current limits of the existing devices and outlining the future developments.

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Integrating humans and robotic machines into one system offers multiple opportunities for creating assistive technologies that can be used in biomedical, industrial, and aerospace applications. The scope of the present research is to study the integration of a human arm with a powered exoskeleton (orthotic device) and its experimental implementation in an elbow joint, naturally controlled by the human. The Human–Machine interface was set at the neuromuscular level, by using the neuromuscular signal (EMG) as the primary command signal for the exoskeleton system. The EMG signal along with the joint kinematics were fed into a myoprocessor (Hill-based muscle model) which in turn predicted the muscle moments on the elbow joint. The moment-based control system integrated myoprocessor moment prediction with feedback moments measured at the human arm/exoskeleton and external load/exoskeleton interfaces. The exoskeleton structure under study was a two-link, two-joint mechanism, corresponding to the arm limbs and joints, which was mechanically linked (worn) by the human operator. In the present setup the shoulder joint was kept fixed at given positions and the actuator was mounted on the exoskeleton elbow joint. The operator manipulated an external weight, located at the exoskeleton tip, while feeling a scaled-down version of the load. The remaining external load on the joint was carried by the exoskeleton actuator. Four indices of performance were used to define the quality of the human/machine integration and to evaluate the operational envelope of the system. Experimental tests have shown that synthesizing the processed EMG signals as command signals with the external-load/human-arm moment feedback, significantly improved the mechanical gain of the system, while maintaining natural human control of the system, relative to other control algorithms that used only position or contact forces. The results indicated the feasibility of an EMG-based power exoskeleton system as an integrated human–machine system using high- level neurological signals.

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This thesis presents the Intelligent Gripper, a low cost instrumented robot finger pad which is equipped with an 8 x 8 tactile sensing array and a 2 x 2 proximity sensing grid. The complete system is composed of three modules. The capacitive tactile sensing array utilizes a dual strip construction to improve its robustness and simplicity, a technology initially developed by Sarcos Research Inc- The proximity network is based on infiared range sensing technology. The microprocessor based inter-face module gives the system intelligent capability. In order to reduce the noise and to improve the system modularity, all electric circuitry is localized. The modular architecture gives the system excellent portability. Following the comprehensive evaluation and characterization of the tactile sensing array and its associated electronic system, an experimental exploration to use the tactile sensor in transient contact force control is presented. It is found that using feedback fiom tactile sensor stabilizes the force control. However, the highest performance for transient force control is achieved from a combined feedback fiom tactile sensor and joint force sensor.

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