Mazhar Iqbal

National University of Sciences and Technology, National University of Science and Technology

Papers

Total Citations

H-Index

About

Mazhar Iqbal is a leading researcher in autonomous robotics, with a primary focus on real-time path planning and obstacle avoidance for mobile robots. His most significant contribution is the development of the **Guided Autowave Pulse Coupled Neural Network (GAPCNN)**—a novel bio-inspired algorithm that addresses a critical challenge in robotics: achieving both speed and optimality in collision-free navigation. While conventional rapid pathfinding algorithms often sacrifice path quality for speed, Iqbal’s GAPCNN framework uniquely guarantees convergence to optimal routes in real time. His seminal 2014 paper on this method has garnered **58 citations**, underscoring its influence in the field. By integrating guided autowave dynamics with pulse-coupled neural networks, his work enables mobile robots to navigate complex environments efficiently, making it highly relevant for applications in autonomous vehicles, warehouse logistics, and search-and-rescue operations. Iqbal’s research stands out for its elegant fusion of neural computation and control theory, offering a practical solution to a long-standing problem in mobile robotics. His contributions continue to inspire new approaches in intelligent navigation systems.