Synthesis of mass-spring networks from high-level code descriptions

Fuente: arXiv
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Main Authors: Omidvar, Parisa, Serra-Garcia, Marc
Format: Preprint
Published: 2025
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author Omidvar, Parisa
Serra-Garcia, Marc
author_facet Omidvar, Parisa
Serra-Garcia, Marc
contents Structural nonlinearity can be harnessed to program complex functionalities in robotic devices. However, it remains a challenge to design nonlinear systems that will accomplish a specific, desired task. The responses that we typically describe as intelligent -- such a robot navigating a maze -- require a large number of degrees of freedom and cannot be captured by traditional optimization objective functions. In this work, we explore a code-based synthesis approach to design mass-spring systems with embodied intelligence. The approach starts from a source code, written in a \emph{mechanical description language}, that details the system boundary, sensor and actuator locations, and desired behavior. A synthesizer software then automatically generates a mass-spring network that performs the described function from the source code description. We exemplify this methodology by designing mass-spring systems realizing a maze-navigating robot and a programmable lock. Remarkably, mechanical description languages can be combined with large-language models, to translate a natural-language description of a task into a functional device.
format Preprint
id arxiv_https___arxiv_org_abs_2511_17588
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Synthesis of mass-spring networks from high-level code descriptions
Omidvar, Parisa
Serra-Garcia, Marc
Other Computer Science
Emerging Technologies
Structural nonlinearity can be harnessed to program complex functionalities in robotic devices. However, it remains a challenge to design nonlinear systems that will accomplish a specific, desired task. The responses that we typically describe as intelligent -- such a robot navigating a maze -- require a large number of degrees of freedom and cannot be captured by traditional optimization objective functions. In this work, we explore a code-based synthesis approach to design mass-spring systems with embodied intelligence. The approach starts from a source code, written in a \emph{mechanical description language}, that details the system boundary, sensor and actuator locations, and desired behavior. A synthesizer software then automatically generates a mass-spring network that performs the described function from the source code description. We exemplify this methodology by designing mass-spring systems realizing a maze-navigating robot and a programmable lock. Remarkably, mechanical description languages can be combined with large-language models, to translate a natural-language description of a task into a functional device.
title Synthesis of mass-spring networks from high-level code descriptions
topic Other Computer Science
Emerging Technologies
url https://arxiv.org/abs/2511.17588