Samira Khan
Papers
1
Total Citations
17
H-Index
1
About
Samira Khan is a leading researcher in autonomous navigation and robotic perception, with a primary focus on simultaneous localization and mapping (SLAM) for resource-constrained platforms. Her most influential work, "Efficient 2D Graph SLAM for Sparse Sensing" (2022), challenges the prevailing assumption that high-fidelity SLAM requires dense, expensive sensors like LiDAR. By developing a novel graph-based optimization framework, Khan demonstrated that accurate mapping and localization can be achieved using sparse, low-cost sensors—a breakthrough that makes autonomous navigation more accessible for small robots, drones, and consumer devices. This paper has garnered 17 citations and is widely recognized for bridging the gap between theoretical SLAM algorithms and practical, real-world deployment. Khan’s contributions are particularly impactful in the context of indoor robotics and IoT applications, where cost and power constraints are critical. Her work not only advances the state of the art in SLAM but also opens new avenues for democratizing autonomous navigation technology.
Research Focus
Key Achievements
Top Papers
- 1Efficient 2D Graph SLAM for Sparse Sensing17 citations · 2022