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This article aims at investigating the global stiffness optimization of a Tricept manipulator and the multi-objective optimization of global stiffness and well-conditioned workspace for 3SPS-S manipulator. Firstly, the genetic algorithm is used to optimize the sum of mean value and the standard deviation of leading diagonal elements of the compliance matrix of the Tricept manipulator to obtain the maximum global stiffness. Secondly, the sum of mean value and standard deviation of leading diagonal elements of the compliance matrix of the 3SPS-S manipulator was used to evaluate the global stiffness and the global condition index was used to evaluate the workspace. The global stiffness and well-conditioned workspace of the 3SPS-S mechanism were optimized simultaneously based on Pareto front theory, and the results show that the stiffness and workspace have increased after optimization.

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