Mohd Yusoff Moh Zuhri
Papers
1
Total Citations
2
H-Index
1
About
Mohd Yusoff Moh Zuhri is a researcher whose work lies at the intersection of robotics and computational optimization, with a particular focus on solving complex kinematic challenges. His primary research areas include robot manipulator control, inverse kinematics, and metaheuristic optimization algorithms. Zuhri’s most notable contribution is the development of an improved spiral search multi-strategy dung beetle optimizer (DBO) algorithm, which he applied to the fundamental robotics problem of inverse kinematics for six-degree-of-freedom manipulators. This work addresses the critical challenge of determining joint angles from a desired end-effector position and orientation—a problem central to robotic arm control and automation. His 2024 paper on this topic has already garnered attention in the field, accumulating 2 citations shortly after publication. By enhancing the DBO algorithm with novel search strategies, Zuhri has provided a more efficient and accurate method for solving inverse kinematics, potentially advancing applications in industrial robotics, manufacturing, and autonomous systems. His research demonstrates a commitment to bridging theoretical optimization techniques with practical engineering problems, making his work valuable for both students exploring robotics and researchers seeking innovative approaches to motion planning and control.
Research Focus
Key Achievements
Top Papers
- 1