Sai Kanna R
Papers
2
Total Citations
28
H-Index
2
About
Sai Kanna R is a rising researcher in robotics, specializing in the complex field of inverse kinematics for industrial manipulators. His work focuses on overcoming the critical challenge of enabling robot arms to accurately follow predefined paths—a necessity for precision tasks in manufacturing and assembly. To solve this, he develops advanced meta-heuristic and hybrid optimization algorithms. His most cited paper, "Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits" (2022, 16 citations), addresses the core problem of controlling manipulator movement under physical joint constraints. Building on this, his second most cited work, "Gravitation search-based hybrid algorithm for solving inverse kinematics of an n-link redundant manipulator" (2023, 12 citations), introduces a novel hybrid algorithm called e3GSA, which leverages the Gravitational Search Algorithm to efficiently handle redundant manipulators. Together, these contributions have earned him over 28 citations, establishing him as a promising voice in optimization-driven robotics. His research offers practical, algorithm-based solutions that push the boundaries of autonomous robotic path planning and control.
Research Focus
Key Achievements
Top Papers
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