Function-based Parametric Co-Design Optimization of Dexterous Hands

2026-04-30

AI Summary

This work addresses the disconnect between dexterous hand design and task-driven control, as well as the limited optimization dimensions in existing approaches, by proposing a unified parametric co-design framework that jointly optimizes palm structure, finger kinematics, fingertip geometry, and surface curvature. Innovatively incorporating fine-grained geometric features—such as surface curvature—into the design space, the method employs a parametric surface deformation kernel to directly model contact interactions, enabling end-to-end simulation-to-reality optimization. Integrating multi-degree-of-freedom finger modeling, task-oriented optimization algorithms, and manufacturability constraints, the approach significantly enhances grasp stability in dynamic manipulation tasks and produces dexterous hand models ready for both simulation and physical fabrication. The resulting designs are open-sourced to advance research in co-design and cross-platform policy transfer.

Abstract

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.

Problem

• dexterous hands
• co-design
• parametric optimization
• grasp stability
• robotic hand design

Innovation

• parametric co-design
• dexterous hand optimization
• surface deformation kernels
• task-driven design
• grasp stability