Javed Ahmad
Papers
2
Total Citations
27
H-Index
2
About
Javed Ahmad is a robotics and autonomous systems researcher whose work focuses on advancing path planning algorithms for mobile robots. His primary contributions lie in optimizing navigation efficiency, safety, and smoothness through novel hybrid approaches. Ahmad’s most-cited paper (2025, 17 citations) integrates Dijkstra’s algorithm with piecewise cubic Bezier optimization, significantly enhancing path safety and trajectory smoothness—a critical improvement for real-world robotic deployments. He further extended this work with the Alpha–Beta Guided Particle Swarm Optimization (ABGPSO) algorithm (2025, 10 citations), which boosts global path planning performance by balancing exploration and exploitation in complex environments. These contributions demonstrate Ahmad’s ability to bridge classical graph-based methods with modern metaheuristic techniques, offering practical solutions for autonomous navigation. His research holds particular relevance for applications in warehouse logistics, search-and-rescue operations, and self-driving vehicles, where reliable and efficient path planning is paramount. With his recent high-impact publications, Ahmad is establishing himself as a promising voice in the field of mobile robotics and computational intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2