Pravakar Roy

Papers

Total Citations

H-Index

About

Pravakar Roy is a leading researcher in agricultural robotics and computer vision, with a focus on automating fruit crop monitoring and yield estimation. His work addresses the critical challenge of enabling robots to accurately count and assess apples in orchard environments using low-cost, low-resolution cameras. Roy’s major contributions include developing vision-based algorithms for apple counting and yield estimation, as demonstrated in his highly cited 2017 paper (16 citations), which provides a foundational method for automated orchard surveying. He also pioneered active view planning strategies, where a robot-mounted camera intelligently selects viewpoints to maximize counting accuracy for apple clusters—a key innovation for real-world deployment. His 2015 work on robotic surveying systems further advanced the field by integrating apple diameter estimation into the counting process, moving beyond expensive active sensors. With a combined citation impact of over 30, Roy’s research has significantly influenced precision agriculture, offering scalable, cost-effective solutions for growers. His notable achievements include developing systems that operate under natural, uncontrolled lighting, making his work highly practical for field applications. For students and researchers, Roy’s contributions exemplify how computer vision and robotics can transform traditional farming into a data-driven, automated industry.