Sahil Modi

International University of the Caribbean, Indian Institute of Technology Bombay

Papers

Total Citations

H-Index

About

Sahil Modi is a robotics researcher whose work spans autonomous agricultural systems and spherical robot locomotion — two domains that reflect a broad commitment to building practical, real-world robotic solutions. His most impactful contribution, "Learned Visual Navigation for Under-Canopy Agricultural Robots" (2021), has garnered 53 citations and addresses a critical gap in precision agriculture: enabling low-cost robots to autonomously navigate beneath crop canopies, performing tasks beyond the reach of drones or large machinery. This work represents a meaningful step toward scalable, intelligent farm automation. Modi's earlier research on spherical robots demonstrates equal ingenuity. His 2019 paper on point-to-point motion planning (21 citations) tackled the inherently complex nonlinear dynamics of spherical locomotion, developing reliable control strategies grounded in experimental observation. Building on this, his 2022 analysis of pendulum-actuated spherical robots explores wobble and precession dynamics, expanding the sensor-mounting possibilities that have historically limited such platforms. Across his career, Modi has accumulated over 75 citations, establishing himself as a thoughtful contributor to mobile robotics and autonomous navigation — particularly in environments where conventional robotic systems struggle to operate effectively.