H. N. Hashmi

National University of Sciences and Technology

Papers

Total Citations

H-Index

About

H. N. Hashmi is a robotics researcher whose work focuses on the control of agile, unstable mobile platforms, with a particular emphasis on ball-bots—highly dynamic robots that balance and maneuver on a single spherical wheel. Hashmi’s key contribution lies in developing advanced control strategies for these inherently unstable systems, which require specialized controllers to achieve high-speed locomotion. In his most-cited work, "Control of a ball-bot using a PSO trained neural network" (2016), Hashmi models the ball-bot as two decoupled, 2-DOF pendulum-on-cart systems—a classical yet challenging control problem. By employing a particle swarm optimization (PSO) algorithm to train a neural network controller, he demonstrates an innovative approach to stabilizing and maneuvering the robot. Although this paper has garnered 2 citations, it represents a foundational step in applying bio-inspired optimization to nonlinear control problems, offering a pathway for future research in agile robotics. Hashmi’s work bridges classical control theory and modern machine learning, making it relevant for students and researchers interested in mobile robotics, nonlinear dynamics, and intelligent control systems.