In this section the spa_optimize_geometric_parameters design tool is used to select design parameters based on the two different applications. Researchers may follow the same procedure using this tool to answer their own design questions.
First, we define the application in terms of quantifiable design criteria constraints. Next, given an initial selection of geometric parameters, the design tool simulates the SPA to determine the selected performance characteristics. Based on the results, the design tool iterates over the parameter space using a COBYLA optimization loop. As there may be several “optimal” solutions, this optimization loop is again embedded within a global-optimization basin-hopping algorithm, which searches for new optimal solutions by permutating the parameters to find new starting points for the COBYLA loop.
In this way multiple unique designs meeting the design criteria can be discovered with only one single starting point from the user. A design is then selected, implemented, and tested experimentally in order to validate the approach. The two case studies presented here show application of the design tool for a multi-test single-optimization of a linear SPA for soft rodent exoskeletons, and a constrained single-test multi-optimization for a bending SPA for soft hand-rehabilitation gloves.