Design and Implementation of a Hybrid-Driven Soft Robot

IF 1.7 4区 工程技术 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Complexity Pub Date : 2024-05-29 DOI:10.1155/2024/7624799
Ke Zhang, Yongqi Bi, Ruiyu Zhang
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引用次数: 0

Abstract

Currently, soft robots alone cannot obtain the same operating speed as rigid robots, while rigid robots are not safe enough for human-robot interaction. To address this problem, this paper describes a hybrid robot system that combines both rigid and flexible systems for unknown domain exploration. The system consists of a four-wheeled robot chassis and a cylindrical pneumatic soft actuator, and finally, a computer is used to coordinate and control both. The hardware of the robot system is designed, a bending motion model is proposed, and SOFA framework is used to carry out finite element simulation (FEM) to verify the reasonableness of the design; linear motion speeds of up to 0.5 m/s, higher than the existing soft robots investigated, were verified experimentally separately after carrying the new module, and steering ability was retained; and the robot carrying the navigation module is verified to have a certain map building and localization function through the construction of the simultaneous localization and mapping (SLAM) experimental platform. The hybrid robot introduced in this paper can move quickly on flat terrain and can use its soft part to avoid wear and tear.

Abstract Image

混合动力软机器人的设计与实现
目前,单靠软体机器人无法获得与硬体机器人相同的运行速度,而硬体机器人在人机交互方面又不够安全。为解决这一问题,本文介绍了一种混合机器人系统,该系统结合了刚性和柔性系统,可用于未知领域的探索。该系统由一个四轮机器人底盘和一个圆柱形气动软执行器组成,最后由计算机对两者进行协调和控制。设计了机器人系统的硬件,提出了弯曲运动模型,并利用 SOFA 框架进行了有限元仿真(FEM),验证了设计的合理性;通过实验分别验证了携带新模块后的直线运动速度可达 0.5 m/s,高于现有的软体机器人,并保留了转向能力;通过构建同步定位与绘图(SLAM)实验平台,验证了携带导航模块的机器人具有一定的地图构建和定位功能。本文介绍的混合机器人可在平坦地形上快速移动,并可利用其柔软部分避免磨损。
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
Complexity
Complexity 综合性期刊-数学跨学科应用
CiteScore
5.80
自引率
4.30%
发文量
595
审稿时长
>12 weeks
期刊介绍: Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.
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