Distributed Control of a Planar Discrete Elastic Rod Model for Caterpillar-Inspired Locomotion

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS

Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9220

Helene Nguewou-Hyousse, William L. Scott, D. Paley

引用次数: 2

Abstract

During crawling, a caterpillar body stretches and bends, and a wave repeatedly travels from the tail to the head. Recently, caterpillar locomotion has been modeled using the theory of planar discrete elastic rods (PDER). This work takes a similar modeling approach and introduces feedback control laws with communication between neighboring segments. Caterpillar locomotion is modeled first as a network of spring-mass-dampers connected through nearest neighbor interactions and then as a network of linked torsional springs. Feedback laws are designed to achieve consensus and traveling wave solutions. Simulation results show the displacement of each segment of a caterpillar during locomotion. These results show promise for the design of feedback control laws in a network model of soft robotic systems.

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平面离散弹性杆模型的毛毛虫启发运动分布控制

在爬行过程中，毛毛虫的身体伸展和弯曲，波浪从尾巴反复传播到头部。近年来，利用平面离散弹性杆理论建立了履带运动模型。这项工作采用了类似的建模方法，并引入了具有相邻段之间通信的反馈控制律。卡特彼勒运动首先建模为通过最近邻相互作用连接的弹簧-质量阻尼器网络，然后建模为连接的扭转弹簧网络。反馈律的设计是为了达成共识和行波解。仿真结果显示了履带在运动过程中各节的位移。这些结果为软机器人系统网络模型的反馈控制律设计提供了前景。

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

Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.40

自引率

66.70%

发文量

期刊介绍： This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.