Hierarchical Performance-Based Design Optimization Framework for Soft Grippers
Fuente:
arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916661443952640 |
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| author | Nohooji, Hamed Rahimi Voos, Holger |
| author_facet | Nohooji, Hamed Rahimi Voos, Holger |
| contents | This paper presents a hierarchical, performance-based framework for the design optimization of multi-fingered soft grippers. To address the need for systematically defined performance indices, the framework structures the optimization process into three integrated layers: Task Space, Motion Space, and Design Space. In the Task Space, performance indices are defined as core objectives, while the Motion Space interprets these into specific movement primitives. Finally, the Design Space applies parametric and topological optimization techniques to refine the geometry and material distribution of the system, achieving a balanced design across key performance metrics. The framework's layered structure enhances SG design, ensuring balanced performance and scalability for complex tasks and contributing to broader advancements in soft robotics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_06294 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Hierarchical Performance-Based Design Optimization Framework for Soft Grippers Nohooji, Hamed Rahimi Voos, Holger Robotics This paper presents a hierarchical, performance-based framework for the design optimization of multi-fingered soft grippers. To address the need for systematically defined performance indices, the framework structures the optimization process into three integrated layers: Task Space, Motion Space, and Design Space. In the Task Space, performance indices are defined as core objectives, while the Motion Space interprets these into specific movement primitives. Finally, the Design Space applies parametric and topological optimization techniques to refine the geometry and material distribution of the system, achieving a balanced design across key performance metrics. The framework's layered structure enhances SG design, ensuring balanced performance and scalability for complex tasks and contributing to broader advancements in soft robotics. |
| title | Hierarchical Performance-Based Design Optimization Framework for Soft Grippers |
| topic | Robotics |
| url | https://arxiv.org/abs/2411.06294 |