Shashikala Gurpur
Papers
1
Total Citations
20
H-Index
1
About
Shashikala Gurpur is a leading researcher at the intersection of intelligent control systems and robotics, with a primary focus on developing advanced algorithms for precise robot-manipulator trajectory tracking. Her most-cited work, "Design and Implementation of Neuro-Fuzzy Control Approach for Robot's Trajectory Tracking" (2023, 20 citations), tackles the critical challenge of minimizing tracking errors, reducing settling time, and curbing overshoot in robotic control. By proposing a novel controller design that integrates neuro-fuzzy approaches, she has made significant contributions to enhancing the accuracy and efficiency of autonomous systems. Her research demonstrates a deep commitment to bridging theoretical control methods with practical implementation, offering robust solutions for real-world robotic applications. Gurpur’s work is particularly impactful for students and researchers in robotics and control engineering, as it provides a clear pathway for improving system performance through intelligent, adaptive algorithms. With a growing citation record, she is establishing herself as a key voice in the field, driving innovation in how robots interact with and navigate complex environments.
Research Focus
Key Achievements
Top Papers
- 1