| Summary: | Flexible intelligent materials have been created by imitating natural intelligence and have been used to create soft robots, such as soft grippers with a wide variety of complicated functions. Compared with traditional rigid grippers, soft grippers are strongly adaptable, have simple grabbing systems, and can grab and manipulate more types of objects. Due to the flexibility of their materials and machinery, their complexity of control is greatly reduced. Accordingly, in this paper, the control of a liquid crystal elastomer, a popular material in the field of soft robots subjected to thermal stimulation, was studied based on its strong adaptability and reversible shape changes. Within a safe temperature range for deformation control analysis, a genetic algorithm was used to optimize proportional–integral–differential parameters, accompanied by establishing a hardware system for real-time temperature measurement and control. Moreover, the previous experimental results were used to design a soft gripper prototype that could capture small and lightweight fragile objects, which provides guidance for the future research and development of soft grippers.
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