This study presents preference-based topological control methods for adjusting the topology optimization designs of a soft (or compliant) gripper. Based on the common occurrences in the current topology optimization that yield same results, minimum design exploration and less control toward user preferred design, adjusting methods are aimed to manipulate topology optimization result toward preference topology while still aim to optimize and improve the gripper performance. The optimized soft gripper is prototyped by 3D printing using thermoplastic elastomer (TPE) material. The optimal designs of inverter mechanism and crunching mechanism using the proposed topological control methods presented in this study are used as design examples. The optimal design of a soft gripper with its preference topology is presented and evaluated between the topology similarity with the preference design and improved performance. Experimental results show that the optimized gripper has larger grip dimension (2.55% more) and higher maximum weight load (250% more) compared with the gripper used as preference. Experiment on gripping objects also show the functional capability of the soft gripper.

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