Fault Detection of Multi-Wheeled Robot Consensus Based on EKF

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS

ACS Applied Bio Materials Pub Date : 2024-07-01 DOI:10.3390/act13070253

A. Jouili, B. Boussaid, A. Zouinkhi, M. N. Abdelkrim

引用次数: 0

Abstract

Synchronizing a network of robots in consensus is an important task for cooperative work. Detecting faults in a network of robots in consensus is a much more important task. In considering a formation of Wheeled Mobile Robots (WMRs) in a master–slave architecture modeled by graph theory, the main objective of this study was to detect and isolate a fault that appears on a robot of this formation in order to remove it from the formation and continue the execution of the assigned task. In this context, we exploit the extended Kalman filter (EKF) to estimate the state of each robot, generate a residual, and deduce whether a fault exists. The implementation of this technique was proven using a Matlab simulator.

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基于 EKF 的多轮机器人故障检测共识

以协商一致的方式同步机器人网络是协同工作的一项重要任务。在达成共识的机器人网络中检测故障则是一项更为重要的任务。考虑到以图论为模型的主从架构中的轮式移动机器人（WMR）编队，本研究的主要目标是检测和隔离编队中出现故障的机器人，以便将其从编队中移除，继续执行分配的任务。在这种情况下，我们利用扩展卡尔曼滤波器（EKF）来估计每个机器人的状态，生成残差，并推断故障是否存在。我们使用 Matlab 仿真器证明了这一技术的实现。

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

ACS Applied Bio Materials Chemistry-Chemistry (all)

CiteScore

9.40

自引率

2.10%

发文量

464

期刊介绍： ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.