Mohammed Misbah Zarrar
Papers
1
Total Citations
5
H-Index
1
About
Dr. Mohammed Misbah Zarrar is a researcher at the forefront of autonomous systems, with a primary focus on end-to-end deep learning for robotic navigation and control. His work addresses a critical gap in the field: while most autonomous navigation solutions rely on camera-based systems, Zarrar has pioneered the use of 2D LiDAR sensors for direct, end-to-end control. His most notable contribution, "TinyLidarNet," introduces a compact deep learning model that enables F1TENTH autonomous racing cars to derive steering and speed commands directly from raw LiDAR data, bypassing traditional mapping and planning pipelines. This work, published in 2024 and already garnering 5 citations, demonstrates that LiDAR-based end-to-end learning can achieve competitive performance while offering advantages in low-light conditions and computational efficiency. Zarrar's research is particularly impactful for resource-constrained platforms, pushing the boundaries of what is possible with minimal sensor suites. His contributions are shaping the next generation of agile, cost-effective autonomous vehicles, making him a rising voice in the robotics and autonomous racing communities.
Research Focus
Key Achievements
Top Papers
- 1