Navid Dinarvand
Papers
1
Total Citations
2
H-Index
1
About
Navid Dinarvand is a robotics researcher specializing in autonomous navigation and real-time optimization for unmanned aerial vehicles (UAVs). His work centers on developing robust Simultaneous Localization and Mapping (SLAM) algorithms that enable indoor flying robots to operate with high precision and low latency. His most-cited paper, "A real time optimization-based SLAM for indoor UAV flying robots" (2021), introduces a novel framework that integrates optimization techniques into SLAM, allowing UAVs to maintain accurate pose estimation and map reconstruction even in GPS-denied environments. This contribution addresses critical challenges in indoor robotics, such as drift and computational efficiency, and has garnered attention for its practical applicability in search-and-rescue, inspection, and warehouse automation. Dinarvand’s research bridges the gap between theoretical optimization and real-world deployment, making his work a valuable resource for students and engineers seeking to advance autonomous flight systems. His ongoing efforts continue to push the boundaries of resilient, real-time perception for agile robots.
Research Focus
Key Achievements
Top Papers
- 1A real time optimization-based SLAM for indoor UAV flying robots2 citations · 2021