| Summary: | 碩士 === 國立成功大學 === 機械工程學系 === 104 === This study presents a systematic optimal design procedure to develop an adaptive compliant gripper (ACG) for grasping objects with various sizes and shapes. A soft-add topology optimization algorithm, reversed bi-directional evolutionary structural optimization (RBESO) considering both geometric advantage and mechanical advantage of the analyzed compliant mechanism, is developed to synthesize the optimal layout of the ACG with better computational efficiency. One special characteristic of the proposed method is that the elements are equivalent to be numerically added into the analysis domain. As the target volume fraction in topology optimization for the analyzed compliant mechanism is usually below 30% of the initial design domain, the traditional methods which remove elements from 100% become inefficient. A size optimization procedure by using a mixed method combing Augmented Lagrange Multiplier (ALM) method and Simplex method is also proposed to maximize the mechanical advantage of the ACG. After the optimal design is obtained, both finite element analysis and experimental tests are carried out to analyze the design. Five ACGs are prototyped using silicon rubber. A performance index for grasping objects with ACGs has also been proposed to evaluate the grasping performance of various designs. The results show the developed ACGS2 gripper is with the highest performance index, which represents the gripper is with better adaptability, faster response, higher payload and stability in overall. The outcomes of this study provide numerical methods for design and analysis of adaptive compliant mechanisms with large deformation and contact nonlinearity, as well as to develop an innovative compliant gripper for grasping objects with geometric inconsistency.
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