Reformist Framework for Improving Human Security for Mobile Robots in Industry 4.0

Anand Singh Rajawat,Pradeep Bedi,Piyush Kumar Shukla,Mohammad Monirujjaman Khan,Aakriti Jain,Atef Zaguia,S B Goyal,Sikandar Ali

doi:10.1155/2021/4744220

Abstract

In this paper, the cooperation between human and robot companies plays a significant role in factories, contributing to greater productivity and efficiency. However, this development breaches established safety procedures when the workspaces are separated from the robot and the human being. These changes have been reflected in industrial robotic safety standards for the last 20 years. We have directed the expansion of a broad field of examination, which focuses on avoiding robotic humans’ effects and minimizing associated risks and consequences. The paper depicts an analysis of prominent safety systems projected and implemented in engineering robotic surroundings that contribute to safe, collective work between humans and robots. Besides, the current regulation has introduced a review and new concepts. The discussion includes multidisciplinary approaches such as estimating and evaluating human-robot collision injuries, mechanical equipment and software to minimize human-robot impacts, impact detection systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model.

Highlights

Anand Singh Rajawat,1 Pradeep Bedi,2 S
Industry 4.0 [1], has emerged that today refers to current manufacturing technology automation and data exchange trends through creating a “smart factory.” e continuous growth in cyber-physical systems internet of things (IoT) and SDN increased computing ability is the foundation of Industry 4.0
We proposed Gaussian Mixture Model (GMM) [33] with expectation maximization (EM). e internet of things (IoT) avoids obstacles by updating its path in real time

Summary

Introduction

Anand Singh Rajawat ,1 Pradeep Bedi ,2 S. E discussion includes multidisciplinary approaches such as estimating and evaluating human-robot collision injuries, mechanical equipment and software to minimize human-robot impacts, impact detection systems, and collision prevention strategies and minimizing their impact to proposed approach for Human Security with Mobile Robots in Industry 4.0 using SDN and CPS with GMM-GM machine learning model.

Results

Conclusion