A Deep Dive into Robot Vision - An Integrative Systematic Literature Review Methodologies and Research Endeavor Practices

Author:

Sultana Saima1ORCID,Alam Muhammad Mansoor2ORCID,Su’ud Mazliham Mohd3ORCID,Mustapha Jawahir Che4ORCID,Prasad Mukesh5ORCID

Affiliation:

1. Universiti Kuala Lumpur (UniKL), Kuala Lumpur, Malaysia, and SZABIST University, Gharo, Pakistan

2. Riphah International University, Islamabad, Pakistan

3. Multimedia University, Cyberjaya, Malaysia

4. Universiti Kuala Lumpur (UniKL), Kuala Lumpur, Malaysia

5. University of Technology Sydney, Sydney, Australia

Abstract

Novel technological swarm and industry 4.0 mold the recent Robot vision research into innovative discovery. To enhance technological paradigm Deep Learning offers remarkable pace to move towards diversified advancement. This research considers the most topical, recent, related and state-of-the-art research reviews that revolve around Robot vision, and shapes the research into Systematic Literature Survey SLR. The SLR considers a combination of more than 100 reviews and empirical studies to perform a critical categorical study and shapes findings against research questions. The research study contribution spans over multiple categories of Robot vision and is tinted along with technical limitations and future research endeavors. Previously multiple research studies have been observed to leverage Robotic vision techniques. Yet, there is none like SLR summarizing recent vision techniques for all targeted Robotic fields. This research SLR could be a precious milestone in Robot vision for each glimpse of Robotics.

Publisher

Association for Computing Machinery (ACM)

Reference153 articles.

1. Artificial Emotional Intelligence in Socially Assistive Robots for Older Adults: A Pilot Study

2. Md. Atiqur Rahman Ahad, Anindya Das Antar, and Omar Shahid. 2019. Vision-based action understanding for assistive healthcare: A short review. In CVPR Workshops. 1–11.

3. O. Amidi, T. Kanade, and J. Miller. 1998. Vision-based autonomous helicopter research at CMU. In Proceedings of Heli Japan, Vol. 98.

4. Mayur Amin and Michael Mabe. 2004. Impact factors use and abuse. International Journal of Environmental Science and Technology.

5. Cognitive System Framework for Brain-Training Exercise Based on Human-Robot Interaction

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3