Rahul Harsha Cheppally

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About

Rahul Harsha Cheppally is an emerging researcher specializing in computer vision and agricultural robotics, with a focus on enabling autonomous navigation in challenging real-world environments. His most notable work, "RowDetr: End-to-end crop row detection using polynomials" (2025), represents a significant contribution to precision agriculture, addressing one of the field's most persistent challenges: reliable crop row detection in GPS-denied, under-canopy environments. By leveraging polynomial representations within an end-to-end detection framework, Cheppally's approach tackles the longstanding difficulties posed by gaps, curved crop rows, and the laborious annotation process that has historically constrained vision-based navigation systems. This work has already garnered 3 citations since its publication, a promising indicator of early community recognition for a recent contribution. Cheppally's research sits at the intersection of deep learning, agricultural automation, and robotic perception — areas of rapidly growing importance as the agricultural sector increasingly turns to autonomous systems for efficiency and scalability. His work reflects a commitment to solving practical, high-impact problems that bridge the gap between advanced machine learning techniques and real-world field deployment, positioning him as a researcher to watch in agricultural AI.