Jho Nathan Singh Kudhal
Papers
1
Total Citations
19
H-Index
1
About
Jho Nathan Singh Kudhal is a robotics researcher whose work lies at the intersection of intelligent control systems and machine vision. His key contributions center on developing adaptive, fuzzy logic-based controllers for robotic manipulators, with a particular focus on enhancing precision and autonomy in pick-and-place operations. His most cited work, "Design and implementation of a fuzzy logic-based joint controller on a 6-DOF robot arm with machine vision feedback" (2017), has garnered 19 citations and demonstrates a practical, integrated approach: combining fuzzy logic control with real-time visual feedback to guide a 4-DOF M100RAK robotic arm. This research is notable for bridging simulation and real-world implementation, offering a cost-effective pathway toward more intelligent industrial automation. Kudhal’s work contributes to the broader field of soft computing in robotics, where traditional control methods are augmented with human-like reasoning. His achievements highlight a commitment to making robotic systems more responsive and adaptable, a critical step toward fully autonomous manufacturing environments. For students and researchers, Kudhal’s research exemplifies how blending control theory with sensory feedback can solve tangible engineering challenges.
Research Focus
Key Achievements
Top Papers
- 1