夹持器
有限元法
参数统计
计算机科学
工程类
3D打印
人工智能
机械工程
结构工程
统计
数学
作者
Mohammad Taghi Rajabi,Sepehr H. Eraghi,Arman Toofani,Shayan Ramezanpour,Preenjot Singh,Jianing Wu,Chung‐Ping Lin,Hamed Rajabi
标识
DOI:10.1088/1748-3190/ae0547
摘要
Conventional rigid grippers remain the most-used robotic grippers in industrial assembly tasks. However, they are limited in their ability to handle a diverse range of objects. This study draws inspiration from nature to address these limitations, employing multidisciplinary methods, such as computer-aided design, parametric modeling, finite element analysis, 3D printing, and mechanical testing.
Computational analysis of three distinct mandible morphs from the stag beetle Cyclommatus mniszechi revealed that key geometric features-specifically mandible curvature and denticle arrangement-govern a functional trade-off between grasping ability and structural safety. This analysis identified a specific morphology optimized for superior grabbing performance, which served as the template for our design.
Leveraging these biological principles, we used parametric modeling to design, and 3D printing to fabricate, a series of novel, mechanically intelligent grippers. Mechanical testing of these prototypes validated our design approach, demonstrating that specific modifications to curvature could significantly enhance the gripper's load-bearing capacity while minimizing object damage. This work establishes a clear pathway from biomechanical analysis to engineered application, offering a robust and cost-efficient blueprint for developing next-generation grippers that operate effectively without complex sensing or actuation systems for tasks in manufacturing, logistics, and healthcare.
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