Papers
20
Total Citations
487
H-Index
10
About
Rekha Raja is a pioneering researcher in agricultural robotics, with a primary focus on precision weed control, machine vision, and robotic manipulation systems. Her work sits at the intersection of computer vision, autonomous systems, and sustainable farming, addressing one of agriculture's most persistent challenges: distinguishing crops from weeds in complex, natural environments. Raja's most influential contribution is her development of real-time weed-crop classification and localization techniques, her top-cited paper earning 159 citations since 2020. Her innovative "crop signalling" concept — using markers such as Rhodamine B fluorescence to enhance crop visibility — has redefined how robots identify plants even in high-density weed environments. Complementing this, she has engineered intelligent sprayer systems, knife-based robotic weed controllers, and stem detection algorithms tailored for crops like lettuce, tomato, and celery. Beyond crop recognition, Raja has made notable contributions to robotic kinematics, developing machine learning frameworks for redundant mobile manipulators and path planning algorithms for rovers navigating uneven terrain. Her 2024 review of agricultural robot software architectures further demonstrates her broad systems-level thinking. With over 450 cumulative citations, Raja's research is shaping the future of autonomous, data-driven precision agriculture.
Research Focus
Key Achievements
Top Papers
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- 3Crop signalling: A novel crop recognition technique for robotic weed control50 citations · 2019
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