In recent years, wearable robots (WRs) for rehabilitation, personal assistance, or human augmentation are gaining increasing interest. To make these devices more energy efficient, radical changes to the mechanical structure of the device are being considered. However, it remains very difficult to predict how people will respond to, and interact with, WRs that differ in terms of mechanical design. Users may adjust their gait pattern in response to the mechanical restrictions or properties of the device. The goal of this pilot study is to show the feasibility of rendering the mechanical properties of different potential WR designs using the robotic gait training device LOPES. This paper describes a new method that selectively cancels the dynamics of LOPES itself and adds the dynamics of the rendered WR using two parallel inverse models. Adaptive frequency oscillators were used to get estimates of the joint position, velocity, and acceleration. Using the inverse models, different WR designs can be evaluated, eliminating the need to build several prototypes. As a proof of principle, we simulated the effect of a very simple WR that consisted of a mass attached to the ankles. Preliminary results show that we are partially able to cancel the dynamics of LOPES. Additionally, the simulation of the mass showed an increase in muscle activity but not in the same level as during the control, where subjects actually carried the mass. In conclusion, the results in this paper suggest that LOPES can be used to render different WRs. In addition, it is very likely that the results can be further optimized when more effort is put in retrieving proper estimations for the velocity and acceleration, which are required for the inverse models.

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In this paper, we present an inexpensive force feedback virtual reality system using a 3-DOF five-bar-linkage manipulator. The direct drive manipulator has a gravity balanced structure. An implicit force control strategy is used to determine the virtual force feedback. The effects of virtual wall and virtual free space controllers are studied. A graphics system is developed to provide the visual feedback to the user. Experimental results are presented to show the user interaction with a virtual wall and a virtual object

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Adaptive tracking techniques are applied to pneumatic muscle actuators arranged in bicep and tricep configurations. The control objective is to force the joint angle to track a specified reference path. Mathematical models are derived for the bicep and tricep configurations. The models are nonlinear and in general time-varying, making adaptive control desirable. Stability results are derived, and the results of simulation studies are presented, contrasting the nonlinear adaptive control to a nonadaptive PID control approach.

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This paper proposes a polyarticular tendon drive system to simulate a variable stiffness of a human fingertip. The stiffness determines displacement of the fingertip when an external force is affected to it. The stiffness should be adjusted not only according to measurement precision of object’s dimensions in order to allow grasping position errors, but also according to tolerance of the assembly in order to allow position errors of assembly components. The variable stiffness therefore contributes to stable grasping and dexterous manipulation. A stiffness of a human fingertip in all directions increases as a grasping force of the human finger increases. The stiffness even in orthogonal direction to a grasping force increases in the same way. Through numerical simulations, feasible parameter settings of our proposed polyarticular tendon drive system are searched and then it is confirmed that the variable stiffness of a robotic finger driven by the proposed polyarticular tendon system is similar to the one of human finger through some experiments.

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