A Deep Dive into Robot Vision - An Integrative Systematic Literature Review Methodologies and Research Endeavor Practices
计算机科学
系统回顾
人工智能
机器人
数据科学
人机交互
梅德林
政治学
法学
作者
Saïma Sultana,Muhammad Mansoor Alam,Mazliham Mohd Su’ud,Jawahir Che Mustapha,Mukesh Prasad
出处
期刊:ACM Computing Surveys [Association for Computing Machinery] 日期:2024-03-01卷期号:56 (9): 1-33被引量:1
标识
DOI:10.1145/3648357
摘要
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.