Papers
1
Total Citations
4
H-Index
1
About
Garima Bisht is a robotics and control systems researcher whose work focuses on intelligent, adaptive control strategies for autonomous mobile robots. Her most-cited paper, "Neural network based adaptive non linear PID controller for non-holonomic mobile robot" (2013, 4 citations), introduces a novel approach for velocity and orientation tracking in nonholonomic robots. In this work, she develops an adaptive PID controller grounded in analog neural networks, where a feedforward neural network is trained online to compute the inverse kinematics of the robot. This contribution is significant for enabling real-time, adaptive control without the need for extensive pre-programmed models, making it highly applicable to dynamic and unstructured environments. While her citation count reflects a focused and emerging impact, her work represents an important step toward integrating neural network-based learning with classical control theory. Bisht’s research is particularly relevant for students and engineers interested in autonomous navigation, intelligent robotics, and the intersection of machine learning and control systems.
Research Focus
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Top Papers
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