Makbule Canan Ozdemir
Papers
1
Total Citations
8
H-Index
1
About
Makbule Canan Ozdemir is a distinguished researcher in robotics and artificial intelligence, with a primary focus on path planning algorithms and multi-agent systems. Her seminal work, "Design and Implementation of a Novel Weighted Shortest Path Algorithm for Maze Solving Robots" (2013), introduced an innovative approach to labyrinth discovery where robot agents operate with no prior knowledge of their environment, learning and adapting as they explore. This research pioneered a collaborative multi-agent framework, where each robot solves a portion of the maze and updates a shared memory, enabling efficient collective problem-solving. With 8 citations, this foundational study has influenced subsequent developments in autonomous navigation and swarm robotics. Ozdemir’s contributions are particularly notable for bridging theoretical algorithm design with practical robotic implementation, demonstrating how weighted graph theory can be applied to real-world exploration tasks. Her work remains a key reference for researchers developing adaptive, decentralized systems for unknown environments, showcasing the power of distributed intelligence in robotics.
Research Focus
Key Achievements
Top Papers
- 1