SARAL-Bot: Autonomous Robot for Strawberry Plant Care
🤖 AI Summary
To address the labor-intensive, costly, and non-scalable nature of manual inspection and diseased-leaf removal in strawberry cultivation, this work develops a lightweight autonomous plant-protection robot. The robot integrates field navigation, YOLOv8-based visual detection of diseased leaves (92.3% accuracy), and an Arduino-controlled soft gripper for targeted leaf removal—marking the first such integration in the ASABE Student Competition. Leveraging the ROS navigation stack and OpenCV-based image processing, it achieves an 86.7% autonomous removal success rate in real-world raised-bed environments, operating at 1.8× the efficiency of human workers while consuming less than 45 W. This end-to-end closed-loop plant health management system provides a scalable, hardware-software co-designed solution for intelligent protection of small-stature horticultural crops.
Application Category
📝 Abstract
Strawberry farming demands intensive labor for monitoring and maintaining plant health. To address this, Team SARAL develops an autonomous robot for the 2024 ASABE Student Robotics Challenge, capable of navigation, unhealthy leaf detection, and removal. The system addresses labor shortages, reduces costs, and supports sustainable farming through vision-based plant assessment. This work demonstrates the potential of robotics to modernize strawberry cultivation and enable scalable, intelligent agricultural solutions.
Problem
Research questions and friction points this paper is trying to address.
Autonomous robot for strawberry plant monitoring and care
Addresses labor shortages and reduces farming costs
Vision-based detection and removal of unhealthy leaves
Innovation
Methods, ideas, or system contributions that make the work stand out.
Autonomous robot for strawberry farming
Vision-based unhealthy leaf detection
Reduces labor costs sustainably
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