An autonomous robotic system using AI and machine vision for precise and efficient plant tissue sampling in greenhouses, enhancing sample integrity and streamlining agricultural research.
The autonomous robotic phenotyping system is designed to revolutionize plant tissue sampling in greenhouse environments. By integrating AI, machine vision, and robotics, this system enhances the precision and efficiency of sampling plant tissues. The technology addresses the inconsistencies and labor-intensive nature of manual sampling by using autonomous ground robots equipped with a dexterous arm and an integrated sensing system. This innovation ensures accurate identification and systematic sampling of specific plants and tissues, thus maintaining sample integrity for advanced agricultural analysis.
Key features:
The system captures images to create 3D models of plant canopies and uses these models to identify and sample target leaves efficiently. The technology is scalable and adaptable, suitable for diverse greenhouse settings and various plant morphologies.
The technology is currently at TRL 4, indicating that it has been validated in a lab setting. The next phases involve optimization through sim-to-sim digital twin processes and field trials in greenhouses to further refine and validate the system's adaptability and efficiency based on real-world feedback.
North Carolina State University is a large, comprehensive public land‑grant research university in Raleigh. Its on‑campus research and technology park co‑locates corporate R&D groups, government partners, and faculty labs, enabling shared facilities, prototyping, and agile contracting. Located in North Carolina’s Research Triangle, partners tap a dense regional ecosystem while engaging through a statewide extension network and a mature co‑op program that deliver field deployment and workforce pipelines. Multiple pilot and demonstration facilities support scale‑up and validation toward pre‑commercial readiness. Research is supported by competitive funding from major federal agencies, including NSF, USDA, DOE, and DOD, and a dedicated technology transfer office with clear IP pathways helps accelerate commercialization.