This paper is focused on designing of fuzzy based gains tuning of proportional-derivative (FTPD) controller for joints positions control of the Asian Institute of Technology’s leg exoskeleton-I (ALEX-I). The main objective of this research is to obtain the desired gait motion of the whole system. The gait data from simulation is used as the input (set point) of ALEX-I, this data is simulated based on body CM balancing criteria. Fuzzy logic controller applies five membership functions of error and rate of error, four KP and three KD singletons output gains are adjusted according with the defined fuzzy rules. The COGS defuzzification output is sent to ARM7 controllers which control all the system joints. The performance of FTPD controller is then compared with the conventional PD controller. The results show superior performance of FTPD in smaller position error, less percentage of power consumption and less oscillation of gait motion on ALEX-I.

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This paper presents an exoskeleton for the assist of forearm motion (elbow flexion-extension and forearm pronationsupination motion) in daily activity and rehabilitation. The exoskeleton is controlled based on the activation patterns of the electromyogram (EMG) signals of the patient’s muscles, which directly reflects the motion intention of the patient, in order to realize natural motion assist The sophisticated real-time neurofuzzy control method, in which the effect of a muscle common to both motions is taken into account, is proposed. The proposed control method enables the cooperative motion of elbow and forearm of the patient by learning the muscle activation patterns of each patient. The effectiveness of the proposed method was evaluated by experiment.

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Robotics, Virtual Reality, Exoskeleton and Human Machine Interface are fields of growing interest and applications every day. Robotic systems have enormous potential to reduce human exposure to dangerous situations and/or increase human presence in remote locations. Most of industrial robots are usually controlled by a computer or micro controllers to perform systematic sequence of actions stored in its memory. Navigation of autonomous robots involves following trajectories generated by automatic motion planners. For non-autonomous systems, the robot’s trajectories are provided by the operator, either trajectories that are pre-set or fed in an on-line fashion, such as teleoperation. Teleoperation is widely used for the direct control of non-autonomous robots from a remote location. The objective of this paper is to facilitate the controlling process by using human-machine interface techniques instead of predefined limited actions in its memory; this is done in order to be able to control the robot arm remotely to discover the World Wide II mines that are still in the western desert of Egypt.

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Haptic rendering has the potential to increase the quality of human-computer interaction with virtual environment by accommodating the sense of touch. In this paper, a 7 DOF arm type exoskeleton device is designed and implemented. Human user can haptically interact with virtual environment by using this light-weight device. The principles of measuring user’s arm motions are presented, which include the dimensional mechanism. The motion of each joint of the proposed haptic device is nearly independent. The virtual contact force is also calculated in real time to meet the stringent requirement of real time haptic rendering. Experiments results show promising feasibility of the arm type exoskeleton device.

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In this paper we present a methodology to drive the end effector of a robotic manipulator, to which is attached a human hand, in order to follow the human’s intention of movement. This set-up is inspired from a neuro-robotics scenario in order to develop systems for restoring motor functionalities in injured and disabled people. Three typical tasks are considered, namely the robot not to interfere with the human’s motion, to assist a person with limited motion capabilities, and finally to be used from the subjects for rehabilitation reasons. The proposed controllers utilize a force control in two different ways, with inner position loop and with inner velocity loop. The derived controllers attempt to incorporate neuro-scientific models results. Also, stability and robust analysis is presented. The properties of the proposed methodology are verified through non-trivial computer simulations

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