Max Robotics — Global Service Robot Directory + US Certification

About

Kaushik Das Sharma is a leading researcher in intelligent control systems, with a primary focus on adaptive fuzzy control, autonomous mobile robot navigation, and robotic manipulator dynamics. His most impactful contribution is a PSO–Lyapunov hybrid stable adaptive fuzzy tracking control approach for vision-based robot navigation, published in 2012 and cited 57 times, which pioneered a novel methodology combining swarm intelligence with Lyapunov stability theory for robust path tracking. He has further advanced the field through harmony search-based adaptive controllers and linear consequence-based fuzzy parallel distributed compensation (PDC) type L₁ adaptive controllers for complex MIMO systems like two-link robot manipulators, addressing time-varying uncertainties and nonlinearities. His work on real-time fractional order L₁ adaptive control strategies for fractional order manipulators, published in 2024, represents a cutting-edge extension into fractional calculus for precision motion control. With over 90 total citations across his most cited works, Das Sharma’s research bridges theoretical control design and experimental validation, as demonstrated in his experimental studies on vision-based navigation. His achievements include developing stable, real-time adaptive controllers that enhance autonomy and reliability in robotics, making significant strides in both simulation and practical implementations for industrial and mobile robotic systems.