Abstract

Robot-assisted femur repair has been of increased interest in recent literature due to the success of robot-assisted surgeries and current reoperation rates for femur fracture surgeries. The current limitation of robot-assisted femur fracture surgery is the lack of large force generation and sufficient workspace size in traditional mechanisms. To address these challenges, our group has created a 3-RRPS parallel mechanism, Robossis, which maintains the strength of parallel mechanisms while improving the translational and rotational workspace volume. In this paper, an optimal design methodology of parallel mechanisms for application to robot-assisted femur fracture surgery using a single-objective genetic algorithm is proposed. The genetic algorithm will use a single-objective function to evaluate the various configurations based on the clinical and mechanical design criteria for femur fracture surgery as well as the global conditioning index. The objective function is composed of the desired translational and rotational workspaces based on the design criteria, dynamic load-carrying capacity, and the homogeneous Jacobian global conditioning index. Lastly, experimental results of Robossis were obtained to validate the kinematic solution and the mechanism itself; Robossis had an average error of 0.31 mm during experimental force testing.

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