Mohammad Dosaranian-Moghadam
Papers
1
Total Citations
2
H-Index
1
About
Mohammad Dosaranian-Moghadam is a researcher specializing in robotics, autonomous navigation, and real-time optimization, with a particular focus on indoor unmanned aerial vehicles (UAVs). His most notable contribution is the development of a real-time optimization-based Simultaneous Localization and Mapping (SLAM) system for indoor UAV flying robots, published in 2021. This work addresses critical challenges in autonomous flight within GPS-denied environments, enabling drones to navigate and map unknown indoor spaces with enhanced accuracy and efficiency. By integrating optimization techniques into SLAM, his research pushes the boundaries of real-time performance, which is essential for applications in search-and-rescue, inspection, and warehouse logistics. Though his work has garnered 2 citations to date, its practical implications for robotics and autonomous systems underscore its potential for future impact. Dosaranian-Moghadam’s contributions highlight a dedication to solving complex, real-world problems in aerial robotics, making his research a valuable reference for students and engineers exploring advanced navigation and control systems.
Research Focus
Key Achievements
Top Papers
- 1A real time optimization-based SLAM for indoor UAV flying robots2 citations · 2021