Ujjal Sarker
Papers
1
Total Citations
13
H-Index
1
About
Ujjal Sarker is a researcher in autonomous robotics and algorithmic path planning, with a focus on map discovery for unknown environments. His most cited work, "A Greedy Approach in Path Selection for DFS Based Maze-map Discovery Algorithm for an autonomous robot" (2012, with 13 citations), addresses a fundamental challenge in robotics: enabling an autonomous robot to efficiently explore and map an unknown maze. Sarker proposed three novel variants of the Depth First Search (DFS) algorithm, integrating a greedy approach to optimize path selection during exploration. This contribution improves upon traditional Breadth First Search (BFS) and DFS methods by reducing redundant traversal and enhancing map discovery speed. His work is particularly relevant to applications in search-and-rescue robotics, warehouse automation, and planetary exploration, where robots must navigate unfamiliar terrains without prior maps. By combining algorithmic efficiency with practical robotic constraints, Sarker’s research offers a scalable solution for real-time navigation. Though his citation count reflects a niche but impactful contribution, his innovative adaptation of greedy heuristics to DFS-based exploration demonstrates a keen understanding of both theoretical computer science and applied robotics.
Research Focus
Key Achievements
Top Papers
- 1