Lang2Morph: Language-Driven Morphological Design of Robotic Hands
Lang2Morph: Language-Driven Morphological Design of Robotic Hands
This research presents Lang2Morph, a framework that uses large language models to map natural-language task descriptions to fabricable robotic hand morphologies within the Open Parametric Hand (OPH) design space. The approach combines task reasoning, structured morphology generation, geometric constraints, and feedback-guided selection to produce task-conditioned hand designs. Morphology-level analyses show high design feasibility and task-dependent structural variation, while real-world experiments with three fabricated hands reveal distinct functional characteristics across manipulation tasks, highlighting the potential of LLMs as practical interfaces for task-driven robotic hand design.
The paper introduces Lang2Morph, an LLM-driven framework that translates natural language task descriptions into fabricable robotic hand morphologies within the Open Parametric Hand design space, supported by morphology-level analyses and real-world experiments with three fabricated hands demonstrating distinct functional characteristics across manipulation tasks.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Source：arXiv Robotics — research abstracts · arxiv.org