基于函数的参数化双工手优化设计
Function-based Parametric Co-Design Optimization of Dexterous Hands
AI总结：
本文提出了一种综合参数框架，统一手掌结构、手指运动学、指尖几何和微尺度表面曲率，通过参数化表面变形核直接影响接触交互，提升抓取稳定性任务的仿真与现实优化性能。
摘要：
尽管在灵活手操作方面取得了进展，但机器人手设计仍然很大程度上与任务驱动的评估和控制脱节，限制了系统化优化。现有的机器人手协同设计方法通常范围有限，仅优化少量设计参数。我们引入了一种综合参数化框架，用于机器人手生成，将手掌结构、手指运动学、指尖几何和细尺度表面曲率统一在一个设计空间中。通过参数化表面变形核引入精细几何特征，直接影响力接触交互。我们验证了该框架在仿真和现实动态场景中的抓取稳定性任务设计优化。我们的框架生成仿真和制造准备的手模型，并将作为开源发布，以加速灵活手协同设计优化框架和跨躯体策略训练和控制研究的快速设计迭代。
英文摘要：
Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting systematic optimization. Existing robotic hand co-design approaches are often limited in scope, optimizing a small subset of design parameters. We introduce a comprehensive parametric framework for robotic hand generation that unifies palm structure, finger kinematics, fingertip geometry, and fine-scale surface curvatures within a single design space. Fine geometric features are introduced through parametric surface deformation kernels that directly influence contact interactions. We validate the framework on design optimization in grasp stability tasks in simulation and real-world dynamic scenarios. Our framework produces simulation- and fabrication-ready hand models and will be released as open-source to enable rapid design iteration for dexterous hand co-design optimization frameworks and cross-embodiment policy training and control research.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
