Numerical Optimization of Underactuated Flexure-Based Grippers

Robotic manipulation in the agri-food industry faces several issues, including object variation, fragility and food safety. Underactuated flexure-based gripper allow passive adaptation to object variation, whilst monolithic flexure joints drive down cost, part-count, hygiene requirements, contamination and wear. However, designing flexure-based grippers presents challenges in achieving sufficient support stiffness, load-bearing capacity and joint deflection. Additionally, modeling the non-linear flexure behavior may become computationally expensive, especially under wide a variety of load cases, limiting the optimization approaches to simple structures and joints. In this work we present an interleaved computational optimization algorithm for underactuated flexure-based grippers, aimed at maximizing the range of graspable circular objects under a given load. This method achieves a superior design faster than state-of-the-art methods that optimize all design parameters simultaneously. A prototype constructed using rapid-prototyping validates the usage of the design method, and experimentally illustrates gripper performance.