Muhammad Firdaus Akbar

Papers

Total Citations

156

H-Index

About

Muhammad Firdaus Akbar is a leading researcher in mobile robotics, specializing in intelligent path planning and navigation for autonomous systems. His work centers on developing novel meta-heuristic optimization algorithms that enable mobile robots to navigate complex, unknown, and dynamic environments with greater efficiency and safety. Akbar’s most impactful contribution is his "Improved genetic algorithm for mobile robot path planning in static environments," which has garnered 107 citations, demonstrating its significance in advancing robotic autonomy. He further expanded the field with his hybrid PSOFS algorithm for unknown indoor settings (43 citations), addressing the critical challenge of real-time navigation without pre-mapped data. His recent work on the Enhanced Firefly Algorithm (EFA) introduces a refined meta-heuristic that outperforms traditional methods in path optimization. Collectively, Akbar’s research bridges theoretical algorithm design with practical robotic applications, providing robust solutions for industries ranging from manufacturing to logistics. His growing citation record and innovative algorithmic approaches mark him as a rising authority in autonomous navigation, offering valuable tools for researchers and engineers seeking to push the boundaries of mobile robot capabilities.