Quinn Sahai
Papers
2
Total Citations
8
H-Index
2
About
Quinn Sahai is a researcher at the intersection of robotics, computer vision, and precision agriculture, with a focus on developing autonomous systems for crop management. Their work centers on enabling agricultural robots to navigate complex field environments and accurately identify harvest-ready produce. In their highly cited 2023 paper, "Path Planning and Mapping of an Autonomous Agricultural Robot Using Robot Operating System (ROS) and Gazebo," Sahai demonstrated how integrating ROS with MATLAB can facilitate real-time mapping and object detection for efficient path following—a foundational contribution that has already garnered 6 citations. Expanding on this, Sahai’s study "Tomato Crop Identification and Recognition for an Autonomous Agricultural Robotic System" introduced a novel shape-based comparison method for distinguishing ripe fruit, achieving 2 citations for its practical approach to reducing computational load in field applications. Together, these works highlight Sahai’s commitment to bridging simulation and real-world deployment, offering scalable solutions for labor-intensive tasks in agriculture. Their research not only advances the capabilities of autonomous ground vehicles but also provides a clear framework for students and engineers seeking to implement ROS-based robotic systems in agricultural settings.
Research Focus
Key Achievements
Top Papers
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- 2