Feeza Khan Khanzada
Papers
1
Total Citations
5
H-Index
1
About
Feeza Khan Khanzada is a robotics researcher focused on advancing autonomous navigation for agricultural applications. Her work bridges the gap between traditional SLAM algorithms and modern deep learning approaches, particularly in outdoor, unstructured environments. In her highly cited 2024 study, she conducted a comprehensive comparative analysis of laser-based and vision-based SLAM systems alongside Deep Neural Network (DNN)-driven Behavior Cloning (BC) for agricultural robots. This research directly tackles the critical challenges of uneven terrain, variable lighting, and dynamic obstacles that hinder autonomous farming equipment. By systematically evaluating these navigation paradigms, Khanzada has provided a foundational framework for developing more robust and reliable field robots. Her contributions are vital for the future of precision agriculture, where autonomous machines must operate safely and efficiently without human intervention. With her work already garnering attention in the robotics community, Khanzada is establishing herself as a key voice in the integration of classical robotics with intelligent learning systems for real-world agricultural deployment.
Research Focus
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Top Papers
- 1