Grey Wolf optimizer for efficient feature selection in robotic systems

Abstract

This paper offers an investigation of Grey Wolf Optimizer (GWO) in robotic systems, using bibliometric data and VOSviewer analysis from 2016 to 2023. These years represent a crucial time in the development of robotic optimization methodologies, as evidenced by 285 documents published by 191 sources, with an annual rate of increase of 49.25%. This growth emphasizes the increasing impact and uses of GWO in the robotics area. The research emphasizes the recency of these documents and their effect, with an average document age of 3.01 years and an average citation count of 9.204 per document. The detailed analysis of 1721 'Keywords Plus' and 826 'Author's Keywords' points to a diverse research landscape, showing GWO in manifold applications, from theoretical background to practical use. Key findings from VOSviewer analysis uncover two primary research streams: robotics and optimization algorithms with GWO in mechanical and control. The high link strength of topics such as 'flexible manipulators' and 'robotic manipulators' reflects an increasing attention to flexibility and accuracy in robotic systems. The presence of the labels 'genetic algorithms' and 'particle swarm optimization (PSO)' together with 'gray wolves' suggests a continuing comparative investigation of optimization techniques. This research not only emphasizes the role of GWO in robotics but also suggests further research areas, suggesting a detailed investigation of GWO application in different robotic types and optimization issues. It gives in-depth view of the current status and future development of GWO in robotics, implying the trend of its further expansion and innovation in this area.