Amit Verma
Papers
1
Total Citations
15
H-Index
1
About
Amit Verma is a researcher whose work sits at the dynamic intersection of industrial automation, evolutionary computation, and intelligent control systems. His research focuses on optimizing complex industrial processes through advanced algorithmic approaches, with a particular emphasis on applying improved genetic algorithms to real-world manufacturing challenges. Verma's most recognized contribution, published in 2022 and already accumulating 15 citations, demonstrates his practical approach to bridging theoretical optimization methods with tangible industrial applications. In this notable work, he leveraged improved evolutionary algorithms to refine process parameter control for industrial robots, utilizing cubic B-spline curve fitting to optimize joint trajectory planning — a contribution with significant implications for precision manufacturing and robotic polishing operations. His research addresses a critical need in modern industry: the ability to fine-tune complex, multi-variable processes that traditional control methods struggle to handle efficiently. By applying bio-inspired computational techniques to industrial robotics, Verma contributes to a growing body of work that promises smarter, more adaptive manufacturing systems. His scholarship will be of particular interest to students and practitioners working in robotics, process control, computational intelligence, and advanced manufacturing optimization.
Research Focus
Key Achievements
Top Papers
- 1