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用于护理环境中模块化机器人快速原型制作的协同设计方法。

Co-design methodology for rapid prototyping of modular robots in care settings.

作者信息

Colle Alexandre, Donaldson Karen, Dragone Mauro

机构信息

Heriot Watt University, Edinburgh, United Kingdom.

Edinburgh Centre for Robotics, Heriot Watt University, Edinburgh, United Kingdom.

出版信息

Front Robot AI. 2025 May 22;12:1581506. doi: 10.3389/frobt.2025.1581506. eCollection 2025.

Abstract

INTRODUCTION

This paper introduces a structured co-design methodology for developing modular robotic solutions for the care sector. Despite the widespread adoption of co-design in robotics, existing frameworks often lack clear and systematic processes to effectively incorporate user requirements into tangible robotic designs.

METHOD

To address this gap, the present work proposes an iterative, modular co-design methodology that captures, organises, and translates user insights into practical robotic modules. The methodology employs Design Research (DR) methods combined with Design for Additive Manufacturing (DfAM) principles, enabling rapid prototyping and iterative refinement based on continuous user feedback. The proposed approach was applied in the development of Robobrico, a modular robot created collaboratively with care home users.

RESULTS

Outcomes from this study demonstrate that this structured process effectively aligns robot functionality with user expectations, enhances adaptability, and facilitates practical integration of modular robotic platforms in real-world care environments.

DISCUSSION

This paper details the proposed methodology, the tools developed to support it, and key insights derived from its implementation.

摘要

引言

本文介绍了一种结构化的协同设计方法,用于开发面向护理领域的模块化机器人解决方案。尽管协同设计在机器人技术中已被广泛采用,但现有的框架往往缺乏清晰、系统的流程,无法有效地将用户需求融入到切实可行的机器人设计中。

方法

为了弥补这一差距,本研究提出了一种迭代式的模块化协同设计方法,该方法能够捕捉、组织用户见解,并将其转化为实际的机器人模块。该方法采用设计研究(DR)方法,并结合增材制造设计(DfAM)原则,基于持续的用户反馈实现快速原型制作和迭代优化。所提出的方法应用于Robobrico的开发,这是一款与养老院用户合作创建的模块化机器人。

结果

本研究的结果表明,这种结构化流程有效地使机器人功能与用户期望相匹配,提高了适应性,并促进了模块化机器人平台在现实世界护理环境中的实际整合。

讨论

本文详细介绍了所提出的方法、为支持该方法而开发的工具,以及从其实施中获得的关键见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59d5/12137090/4edff4cf2172/frobt-12-1581506-g001.jpg

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