Md. Sazzad Mahmud
Papers
1
Total Citations
13
H-Index
1
About
Md. Sazzad Mahmud’s research centers on autonomous robotics and algorithmic path planning, with a particular focus on maze exploration and map discovery. His most cited work, “A Greedy Approach in Path Selection for DFS Based Maze-map Discovery Algorithm for an autonomous robot” (2012, 13 citations), introduces three novel variants of the Depth First Search (DFS) algorithm that incorporate greedy path selection to improve efficiency in unknown environments. This contribution addresses a fundamental challenge in robotics—how an autonomous agent can systematically discover and map an unknown maze without prior knowledge. By integrating greedy heuristics with classical DFS, Mahmud’s approach reduces redundant exploration and optimizes traversal, offering practical improvements over standard BFS and DFS methods. His work has been cited by researchers in swarm robotics, autonomous navigation, and search-and-rescue systems, demonstrating its relevance to real-world applications. Mahmud’s research exemplifies how algorithmic innovation can directly enhance robotic autonomy, making his contributions valuable for students and engineers working on intelligent navigation systems.
Research Focus
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Top Papers
- 1