Location: Application Technology Research
Project Number: 5082-30500-001-075-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Sep 15, 2025
End Date: Sep 14, 2026
Objective:
1. Develop a computer vision framework using artificial intelligence to enable prototype greenhouse robots to perform multiple farm practice tasks.
2. Detect and classify plant diseases in real time under varying greenhouse lighting and plant conditions.
3. Support autonomous navigation through visual input by optimizing path planning based on plant geometry and environmental obstacles.
4. Enable vision-guided crop harvesting through the integration of object detection and robotic manipulation algorithms.
5. Provide visual data analysis to support yield forecasting by estimating plant load and fruit development over time.
Approach:
1. This research provides U.S. greenhouse growers innovative AI-based technologies for real-time plant health monitoring, accurate yield estimation, and precision crop management. The integrated system is designed to support data-driven decision-making and promote efficient, high-quality production in controlled environment agriculture.
2. An optimized harvesting mechanism will be implemented to allow the robotic manipulator to selectively harvest crops that meet economic thresholds and market quality standards.
3. A yield estimation solution will be developed using time-series image data to analyze plant growth stages and productivity trends.
4. All system components will be validated through repeated trials in controlled environment agriculture settings to assess accuracy, reliability, and operational efficiency.