Hasibul Majid
Papers
1
Total Citations
10
H-Index
1
About
Hasibul Majid is a robotics researcher whose work centers on intelligent navigation and path planning for autonomous mobile robots operating in complex, dynamic environments. His most-cited paper, "An Efficient Potential-Function Based Path-Planning Algorithm for Mobile Robots in Dynamic Environments with Moving Targets" (2015), introduces a novel approach that adapts classical potential field methods to handle moving obstacles and targets—a critical challenge for real-world robotic deployment. This work, with 10 citations, has influenced subsequent studies in collision avoidance and real-time trajectory generation. Majid’s contributions are particularly valuable for applications in warehouse logistics, search-and-rescue, and autonomous driving, where robots must continuously replan paths in unpredictable settings. By addressing the limitations of traditional potential functions—such as local minima and oscillatory behavior—his algorithm offers a computationally efficient solution that balances safety and goal-reaching performance. His research underscores a commitment to bridging theoretical control theory with practical robotic systems, making him a notable figure in the field of mobile robot autonomy.
Research Focus
Key Achievements
Top Papers
- 1