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Augmented variable center of rotation in controlling a robotic walker to adapt user characteristics

This paper propose a new control algorithm for a robotic walker based on augmented variable center of rotation (COR) to adapt to user's controlling characteristics. The new CORs are taken from environment-based training. This is done by allowing the user to use the robotic walker from a start point to a goal point in a training environment and path following algorithm is employed. The user's intention represented by applied force/torque is logged during training. The logged data is segmented to correspond to the straight and curve segments in the training environment. This data is used to regenerate the path of the robotic walker. The error between the regenerated and the desired path is taken and in case a large path error exists, an optimization program is used to change the COR until the sum of the square of the path error is minimized. This approach refers to an offline COR determination. A variable COR controller as a function of applied torque is designed based on the new CORs. This is augmented and used in the actual control of the robotic walker. The proposed control algorithm was experimentally implemented and results show its validity.