Machine Vision in the Context of Robotics: A Systematic Literature Review
This review provides an overview of current challenges in machine vision for robotics, useful for researchers to identify future directions, but it is incremental as it synthesizes existing work without new methods or data.
The paper conducted a systematic literature review of machine vision in robotics over the last 10 years, analyzing 52 relevant papers and identifying that while robustness and computation time have improved, occlusion and lighting variance remain major challenges.
Machine vision is critical to robotics due to a wide range of applications which rely on input from visual sensors such as autonomous mobile robots and smart production systems. To create the smart homes and systems of tomorrow, an overview about current challenges in the research field would be of use to identify further possible directions, created in a systematic and reproducible manner. In this work a systematic literature review was conducted covering research from the last 10 years. We screened 172 papers from four databases and selected 52 relevant papers. While robustness and computation time were improved greatly, occlusion and lighting variance are still the biggest problems faced. From the number of recent publications, we conclude that the observed field is of relevance and interest to the research community. Further challenges arise in many areas of the field.