Modeling and control of a transfemoral prosthesis embedding two infinitely variable transmissions.

In this paper, we report the model of an original actuation concept for a transfemoral prosthesis, relying on the combination of a single power motor, a compliant element (a spring), a mechanical differential, and two infinitely variable transmissions. It allows to manage the mechanical power flows through the device in both directions (i.e. when energy should be produced or dissipated by the knee and ankle), so that the power motor does not face the sharp load power fluctuations. The paper further reports a preliminary approach to synthesize a closed-loop controller for this device, and simulation results of this closed-loop behavior for three locomotion tasks: level-ground walking and stair ascent/descent. These results illustrate the capacity of this actuation principle to filter the load power profile, and further highlight the necessity to maximize the mechanical efficiency of each part of this actuation scheme.

Adaptive position anticipation in a support robot for overground gait training enhances transparency.

Rehabilitation robots being developed nowadays rely on force and/or impedance control. This is guided by clinical evidence showing better performance if the patient is left with the capacity to influence the robot trajectory. The simplest, yet fundamental, mode of force control is when the robot has to be transparent, i.e. to apply no forces/torques on the patient. This mode is useful both in scenarios where the robot has to apply pinpointed support during some training phases and be transparent otherwise, and for any force controller in general, to avoid the reference forces to be polluted by the robot own dynamics. This contribution proposes a method to improve transparency on a support robot for overground training. The method consists in learning the patient's movement by using adaptive oscillators and then anticipate its future evolution in order to synchronize the robot movement. In experiments with human subjects walking in the gait support robot FLOAT, this method can decrease the undesired oscillations of the support force applied to the human user by up to 50%.