Satisfying Task Completion and Assist-as-Needed Performance in Robotic Exoskeletons

Assist-as-needed (AAN) control approaches aim to minimize the intervention of robots in robot-aided rehabilitation therapy when patients are able to perform the task. The existing approaches generally contain a forgiving controller which fails to satisfactorily complete the task when patients stay passive or apply resistive/opposing forces. Task completion in such situations is important since it efficiently trains and guides users on how to perform the exercise during active participation. In this study, we have developed an AAN control scheme that provides significant freedom to users when they can perform the exercise while it provides sufficient support for the precise completion of the task when users are not able to do so. These features have been achieved by modulating the impedance of the robot and designing the controller in the velocity domain. A new velocity tracking controller is proposed which does not utilize velocity measurements, and two methods are considered to measure human inputs: force sensor-based method and disturbance observer-based method. In the first approach, the controller does not require the dynamics of the human-robot system, and in the second approach, partial information of the dynamics is required. The performance of the controller is evaluated on an upper-limb robotic exoskeleton.

Automated summary

The study proposes an AAN control scheme that provides users with freedom when performing exercises and support when needed, using a new velocity tracking controller and two methods for measuring human inputs. The performance of the controller is evaluated on an upper-limb robotic exoskeleton.