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The growing interest in the use of parallel manipulators in machining applications requires clear determination of the workspace and dexterity. In this paper, the workspace optimization of a Tricept parallel manipulator under joint constraints is performed. This parallel manipulator has complex degrees of freedom and, therefore, leads to dimensionally inhomogeneous Jacobian matrices. Here, we divide the Jacobian entries by units of length, thereby producing a new Jacobian that is dimensionally homogeneous. By multiplying the associated entries of the twist array to the same length, we made this array homogeneous as well. The workspace of the manipulator is parameterized using several design parameters and is optimized using a genetic algorithm. For the workspace of the manipulator, local conditioning indices and minimum singular values are calculated. For the optimal design, it is shown that by introducing the local conditioning indices and minimum singular values, the quality of the parallel manipulator is improved at the cost of workspace reduction.

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