Gajanan Nikhade

Papers

Total Citations

H-Index

About

Gajanan Nikhade is a robotics researcher whose work lies at the intersection of mobile robot control, industrial automation, and intelligent trajectory generation. His most cited paper, "Robust Trajectory Tracking Control for an Omnidirectional Mobile Robot" (2017, 6 citations), addresses the growing demand for high-mobility robots in competitive and industrial settings, proposing a robust control strategy that enhances tracking accuracy. Nikhade also explores human-robot collaboration through "Imitation Learning in Industrial Robots" (2017, 3 citations), where he develops a teleoperation-based trajectory planner that enables robots to learn directly from human arm motion—a simplified yet effective approach to skill transfer. Earlier, in "Adaptive Neuro Fuzzy Inference System (ANFIS) for Generation of Joint Angle Trajectory" (2013, 3 citations), he demonstrated how fuzzy logic and neural networks can generate smooth joint trajectories with minimal mathematical modeling, paving the way for more adaptive robotic systems. Though his citation counts are modest, Nikhade’s contributions are foundational in advancing practical, learning-based control for both mobile and industrial robots. His work is particularly relevant for researchers interested in robust control, imitation learning, and intelligent automation.