Magnetically actuated millimeter-scale biped

IF 4.3 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Robotics and Autonomous Systems Pub Date : 2025-03-25 DOI:10.1016/j.robot.2025.104985

Adam Cox, Farshid Asadi, Ammar Yacoub, Sinan Beskok, Yildirim Hurmuzlu

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引用次数: 0

Abstract

This paper presents a novel approach to studying bipedal locomotion using magnetically actuated miniature robots. Traditional bipedal locomotion machines are expensive and complex. In contrast, we introduce “Big Foot”, a lightweight 0.3 g robot designed to explore fundamental concepts of bipedal locomotion without requiring complex hardware.

We introduce a novel design and actuation mechanism for the magnetically actuated miniature robot, followed by a numerical model to analyze its dynamics and stability. Two actuation schemes are investigated: heel strike-based and constant period actuation. Heel strike-based actuation provides superior stability, consistent gait generation, and faster locomotion, while constant period actuation excels on steeper slopes. Experimental validation with Big Foot confirms successful uphill gait generation and trajectory tracking. Additionally, we highlight the potential scalability of our approach, proposing an extension to a design similar to an inertially actuated larger-scale biped without joint actuation at the ankles or hips.

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磁驱动毫米级两足动物

本文提出了一种利用磁驱动微型机器人研究两足运动的新方法。传统的双足运动机器既昂贵又复杂。相比之下，我们介绍了“大脚”，一个重量为0.3克的轻型机器人，旨在探索两足运动的基本概念，而不需要复杂的硬件。介绍了一种新型磁驱动微型机器人的设计和驱动机构，并建立了其动力学和稳定性的数值模型。研究了两种驱动方案：基于跟向驱动和恒周期驱动。基于脚跟撞击的驱动提供了优越的稳定性，一致的步态生成和更快的运动，而恒定周期驱动在更陡峭的斜坡上表现出色。实验验证与大脚证实了成功的上坡步态生成和轨迹跟踪。此外，我们强调了我们的方法的潜在可扩展性，提出了一个类似于惯性驱动的大型双足动物的设计扩展，没有脚踝或臀部的关节驱动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Robotics and Autonomous Systems 工程技术-机器人学

CiteScore

9.00

自引率

7.00%

发文量

164

审稿时长

4.5 months

期刊介绍： Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.