Yash Agarwal
Papers
1
Total Citations
4
H-Index
1
About
Yash Agarwal is a researcher at the intersection of robotics, computer vision, and sustainable agriculture, with a focus on developing low-cost, energy-efficient autonomous systems. His most cited work, "A Proposal of FPGA-Based Low Cost and Power Efficient Autonomous Fruit Harvester" (2020, 4 citations), introduces a novel robotic harvester that integrates fruit detection, odometry, localization, and deep learning with a custom end-effector design. This work addresses critical challenges in agricultural automation—balancing computational efficiency with real-world deployment constraints—by leveraging FPGA-based processing to minimize power consumption while maintaining robust performance. Agarwal’s contributions are particularly notable for their emphasis on accessibility and scalability, aiming to make precision agriculture viable for smaller-scale farms. His research demonstrates a practical pathway toward reducing labor costs and food waste through intelligent, autonomous fruit plucking. Though early in his career, his work signals a promising trajectory in embedded AI for field robotics, combining hardware-software co-design with applied machine learning to solve pressing agricultural challenges.
Research Focus
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Top Papers
- 1