The unique human-machine integral system of lower extremity carrying exoskeleton system calls for the similar structure for the human and the exoskeleton, which can simply the stability analysis, but the exoskeleton structure becomes complex. At the same time, the effective lower extremity carrying exoskeleton control method, that is, virtual torque control method demands the exact mass attributes. For the complex mechanism structure, the mathematics model can not be built easily. In this paper, the virtual prototyping software ADAMS is introduced to model the exoskeleton and simulate the kinematics and dynamics, which solve the above problems perfectly.

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Exoskeletons are structures of rigid links mounted on the body that promise to restore, rehabilitate, or enhance the human motor function. A major challenge in the practical use of exoskeletons for daily activities relate to the coupled control of human-exoskeleton system. This paper provides a method to resolve the control problem by relegation of the human control andexoskeleton control to two control subsystems. The first subsystem represents the execution of voluntary control from commands generated from the central nervous system. This subsystem is responsible primarily for the kinetic or dynamic components of the motion, including motion generation. The second subsystem represents the exoskeleton controller, responsible for joint level accommodation of all gravitational, static, and certain reactive forces. If all such forces are static, the exoskeleton controller can be viewed as a compensator that maintains the body in static equilibrium. The proposed strategy provides a clear partition between natural voluntary control by the CNS, and artificial assist by the exoskeleton controller. Two methods are presented for implementation of the proposed control algorithm. The first method is based on the principal of virtual work. The second method is a recursive algorithm based on force and moment balance equations. Analytical results are presented to study feasibility regions of exoskeleton control strategies in terms of mechanical efficiency. Finally, simulation results are presented to demonstrate the efficacy of the algorithm for a powered ankle-foot orthosis application.

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This paper presents a method of intelligent perception assist (IPA) with optimum force vector modification for an upper-limbexoskeleton robot to assist the perception of the user to interact with environment in addition to power-assist. The exoskeletonassists not only the motion but also the perception of the user. In the case of perception assist, the exoskeleton assists user to interact with the environment by monitoring the userpsilas interaction with the environment. The exoskeleton is equipped with a sonar sensor and a stereo camera to gain information on the userpsilas interaction with the environment. When the user interacts with the environment, if the exoskeleton found any problem in the userpsilas motion, the optimum force vector modification (i.e., the modification of power-assist force vector with the optimum amount of force) is carried out by the exoskeleton to modify the userpsilas motion to solve the problem without giving any uncomfortable feeling to the user due to motion modification. IPA ensures that the userpsilas interaction with the environment can be monitored by the camera all the time by rotating the camera to track the location of the userpsilas hand. The effectiveness of the proposed concept was experimentally evaluated.

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We developed a passive exoskeleton that was designed to minimize joint work during walking. The exoskeleton makes use of passive structures, called artificial tendons, acting in parallel with the leg. Artificial tendons are elastic elements that are able to store and redistribute energy over the human leg joints. The elastic characteristics of the tendons have been optimized to minimize the mechanical work of the human leg joints. In simulation the maximal reduction was 40 percent. The performance of the exoskeleton was evaluated in an experiment in which nine subjects participated. Energy expenditure and muscle activation were measured during three conditions: Normal walking, walking with the exoskeleton without artificial tendons, and walking with the exoskeleton with the artificial tendons. Normal walking was the most energy efficient. While walking with the exoskeleton, the artificial tendons only resulted in a negligibly small decrease in energy expenditure.

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The lower extremity exoskeleton is a wearable device that can increase the strength, speed, and endurance of the wearer. In order to let the exoskeleton moving at desired trajectories, an accurate kinematics model of the mechanism is required. As theexoskeleton has many degrees of freedom (DOFs) and has no fixed base, it is difficult to analyze the kinematics by using conventional methods. In this paper, a generalized kinematics model of lower extremity exoskeletons is proposed by employing coordinate transforming matrix. Meanwhile, the formulation of forward kinematics and the inverse kinematics are discussed in detail. Finally, gait planning is realized according to the results of kinematics analysis. The commercialized dynamics analysis software ADAMS was selected for the modeling and simulation of the generalized lower extremity exoskeleton. To verify the theoretical analysis, a virtual low extremity exoskeleton is built. Based on the inversed kinematics of low extremity exoskeleton, the virtual prototype walks stably in ADAMS by controlled by MATLAB SIMULINK for tracking a desired gait data.

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