To complete the control of exoskeleton carrying robot perfectly, the human-machine interaction forces model should be identified, which can be simulated using spring-damper model, that is, the coefficient elasticity and damping should be gotten. For the coupling of the several joints, the parameters should be optimized from the system global performance. In this paper, estimation of distribution algorithm(EDA) is used to identification interaction parameters. Second-order EDA based on general structure Gauss network is introduced to replace the condition probability density function, the crossover and mutation operators are added to speed the evolution process. Combining the individual energy-entropy selection, the detail human-machine interaction forces identification method using the improved estimation of distribution algorithm is given and the human-machine carrying robot control system simulation results show the validity of the method.

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This paper presents the design, and performance of a high fidelity three degree-of-freedom wrist exoskeleton robot, for neuroscience study, training and rehabilitation. The IIT-Wrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuriesIn the present paper the IIT-Wrist haptic robot is described in terms of kinematics and haptics features to meet specific requirements for a safety human.machine interaction. In relation with a feasibility study in the field of robot therapy a preliminary training of stroke patient was perfrormed. The task consisted in tracking a target using one degree of freedom at time: Flexion/Extension, adduction/abduction, pronation/supination separately. The target motion is harmonic and tracking is aided by a suitable force field. The preliminary study with three patients shows the stability and the efficacy of the control scheme.

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In this paper we introduce the use of force feedback in conjunction with myoelectric control to establish an improved interface for a powered prosthetic limb. The force feedback is delivered through a single-axis exoskeleton worn about the elbow, while the EMG signal is derived from the biceps muscle. This combination is intended to produce a sense of effort in the biceps that is associated with the action of the motorized prosthetic gripper. The method engages both efferent and afferent signals innervating a functional muscle with the aim of realizing a muscle that is effectively biarticular. The controlling muscle spans one joint physiologically and a second, prosthetic joint functionally. Preliminary experiments have demonstrated that force feedback can substitute for vision during grasp and lift tasks.

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The hand force feedback system is an anthropomorphic haptic interface for the replication of the forces arising during grasping and fine manipulation operations. It is composed of four independent finger dorsal exoskeletons which wrap up four fingers of the human hand (the little finger is excluded). Each finger possesses three electrically actuated DOF placed in correspondence with the human finger flexion axes and a passive DOF allowing finger abduction movements. Each exoskeleton finger has three points of attachment to the operator’s finger (two for the thumb) at the middle of the phalanges. Mechanical fixtures guarantee that just a force perpendicular to the finger and in its sagittal plane is exchanged at each point of attachment. Such force component is sensed and it is actively controlled in feedback. The paper illustrates the design and testing of the controller for the thumbexoskeleton. First the mechanical system is analyzed and the features which influence the controller design, such as the presence of unidirectional tendon transmission, are modeled. Then haptic controllers, i.e. feedback controllers aiming at improving the performance of the device when used as a haptic interface for virtual environments or telemanipulation, are designed and tested experimentally. Finally the experimental results are discussed

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This paper outlines a novel approach of displaying multifingered tactile feedback information from remote and virtual environments. Miniature tactile fingertip modules are developed allowing multi-fingered integration into an already existing hand force exoskeleton for display of combined tactile and kinesthetic feedback. The tactile feedback comprises generation of both, vibrotactile and thermal stimuli directly at the operator’s fingertip where a multitude of human tactile receptors are located The proposed parallel configuration of integrated vibration and heat display with combined kinesthetic feedback actuators considers a novel approach towards the generation of holistic haptic sensations. Corresponding tactile rendering algorithms are presented computing realistic tactile stimuli of object properties from either remote real or virtual environments. Moreover the article discusses the design of a developed thermal and texture sensor with corresponding data processing algorithms for online identification of tactile object properties in a remote environment. The new quality of generated multi-fingered tactile feedback was evaluated in several experiments enabling a human operator performing exploratory tasks.

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