AI-enabled autonomous robot designed for efficient plant tissue sampling in greenhouses. Utilizes machine learning for plant identification, robotic grippers for sampling, and advanced navigation techniques for seamless operation.
The proposed solution is an AI-enabled autonomous robot designed to revolutionize plant tissue sampling in greenhouse environments. By integrating advanced machine learning models, the robot can accurately identify plant species and specific tissues for sampling. This innovation aims to enhance efficiency and precision in agricultural research and commercial greenhouse operations by automating the labor-intensive process of tissue sampling.
Key features:
Currently at Technology Readiness Level (TRL) 2, the solution is in the concept and formulation stage. Future validation plans include enhancing plant image databases using Generative Adversarial Networks (GAN) and refining detection algorithms to improve robustness and accuracy.
Indiana University is a comprehensive public research university system serving the state through flagship and urban campuses and a broad mix of liberal arts and professional programs. Industry engagement is anchored by integration with a major hospital system and a large medical school, enabling clinical access and translational pathways in Indianapolis. Co-located labs, corporate-sponsored capstones, and internship pipelines connect companies with faculty and student talent across a statewide campus network. Research is supported by competitive funding from agencies such as the NIH, NSF, and the U.S. Department of Defense, along with state and industry partners. A dedicated technology transfer office and venture arm provide IP management, licensing, and startup support.