Alok Deep

National Institute of Technical Teachers Training and Research

Papers

Total Citations

H-Index

About

Alok Deep’s research focuses on the intersection of robotics, control systems, and embedded automation, with a particular emphasis on mobile robot navigation and platform stabilization. His most cited work, “Robotic arm controlling using automated balancing platform” (2015, 4 citations), demonstrates an innovative use of low-cost Arduino-based systems to achieve real-time disturbance compensation—a practical contribution to accessible robotics. More recently, his 2025 paper “Comparison of Various Control Techniques for Path Control of Mobile Robots” (1 citation) systematically evaluates PID, adaptive, sliding mode, and model predictive controllers for maintaining trajectory under random disturbances, offering valuable comparative insights for autonomous navigation. While his citation counts are modest, Deep’s work is notable for bridging theoretical control strategies with affordable prototyping platforms, making advanced robotics concepts more approachable for students and hobbyists. His research underscores the importance of robust control in real-world robotic applications, from industrial automation to educational toolkits.