Nazmuzzaman Khan
Papers
3
Total Citations
53
H-Index
2
About
Nazmuzzaman Khan is a robotics and precision agriculture researcher whose work bridges autonomous navigation, computer vision, and smart farming systems. His most impactful contribution, "GPS Guided Autonomous Navigation of a Small Agricultural Robot with Automated Fertilizing System" (2018, 48 citations), demonstrates a fully integrated robot capable of GPS-based path planning, weed detection via color segmentation, and targeted herbicide spraying—a practical step toward reducing chemical use in agriculture. Khan also advances crop row detection, developing clustering algorithms that handle both straight and curved rows under variable field conditions (2021, 4 citations; 2020, 1 citation). These vision-based methods are critical for enabling agricultural robots to navigate reliably without GPS in dense canopies. His work directly addresses two core challenges in field robotics: robust perception under natural variation and autonomous task execution. By combining mechatronic design with algorithmic innovation, Khan’s research supports the broader goal of sustainable, data-driven farming. His contributions are especially relevant for students and engineers working on low-cost, scalable agricultural robots for smallholder farms.
Research Focus
Key Achievements
Top Papers
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