Evolutionary Optimization of Ground Reaction Force for a Prosthetic Leg Testing Robot
American Control Conference
Transfemoral amputees modify their gait in order to compensate for their prosthetic leg. This compensation causes harmful secondary physical conditions due to an over-dependence on the intact limb and deficiencies of the prosthesis. Even with more advanced prostheses, amputees still have to alter their gait to compensate for the prosthesis. We present a novel way to quantify how much an amputee has to compensate for a prosthetic leg. We train a newly-developed prosthetic leg testing robot to walk with a prosthesis using an evolutionary algorithm called biogeography-based optimization (BBO). The robot is initially commanded to follow able-bodied hip and thigh trajectories, and BBO then modifies these reference inputs. We adjust the reference inputs to minimize the error between the ground reaction force (GRF) of able-bodied gait data, and that of the robot while walking with the prosthesis. Experimental results show a 62% decrease in the GRF error, effectively demonstrating the robot's compensation for the prosthesis.
Davis, R.; Richter, Hanz; Simon, Daniel J.; and van den Bogert, Antonie J., "Evolutionary Optimization of Ground Reaction Force for a Prosthetic Leg Testing Robot" (2014). Electrical Engineering & Computer Science Faculty Publications. 347.
R. Davis, H. Richter, D. Simon and A. van den Bogert, "Evolutionary optimization of ground reaction force for a prosthetic leg testing robot," in 2014 American Control Conference, 2014, pp. 4081-4086.