SBIR Phase II: Full-Scale Demonstration of Autonomous Robotic Greenhouse for Sustainable Local Food Production

SBIR 第二阶段：用于可持续当地粮食生产的自主机器人温室的全面示范

• 批准号: 2233520
• 负责人: David Ashton
• 金额: $ 100万
• 依托单位: CANOPII INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2233520&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Full; Scale

The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project promotes small and mid-sized farming in the United States through environmentally friendly means. Through cost-effective labor automation, a fully automated, turn-key greenhouse production system can be made more accessible. This project will provide farmers with a tool that can guarantee a baseline annual production of leafy greens and herbs, independent of weather variables and labor accessibility. By removing weather limitations and labor requirements, small and mid-sized farms can be made more profitable and scalable. This project will have a positive impact on the advancement of local and regional food systems. By advancing a market that has been historically ignored from a technological standpoint, an attractive alternative to large-scale industrial agriculture and foreign fresh food imports will be created. Making small and mid-sized farms more economically viable will create a more robust and sustainable food system. This SBIR Phase II effort will design, build, and demonstrate a full-scale, automated greenhouse farm prototype. This prototype will remain completely autonomous for weeks at a time requiring no humans to enter the farm while all processes from seed to storage of harvested crops are performed robotically. No greenhouse technology, at any price point, has been able to demonstrate an ability to achieve this degree of automation. This technology will advance the implementation of robotics in food production by addressing the capital costs, labor, and energy barriers that controlled environment agriculture systems currently face. Key challenges include the production of approximately 340 plants per day without any human intervention, a low-cost design for setup and ongoing operations, and the ability to adjust product outputs in real-time to meet market demands. Human interaction with the growing process will be limited through a high degree of system automation, including computer vision for plant inspections and self-cleaning processes. Novel plant growth and handling processes will allow for virtually any type of leafy green or herb to be grown. A variety of sensors will be used to monitor conditions and adjust the system, allowing fresh produce in areas without suitable agricultural opportunities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一小企业创新研究（SBIR）第二阶段项目的更广泛/商业影响通过环保手段促进了美国中小型农业。通过具有成本效益的劳动力自动化，可以使全自动化的交钥匙温室生产系统更容易使用。该项目将为农民提供一种工具，可以保证绿叶蔬菜和草药的基线年产量，不受天气变化和劳动力可及性的影响。通过消除天气限制和劳动力需求，中小型农场可以变得更加有利可图和可扩展。该项目将对地方和区域粮食系统的发展产生积极影响。通过推进一个从技术角度来看一直被忽视的市场，将创造一个有吸引力的替代大规模工业化农业和外国新鲜食品进口的选择。使中小型农场在经济上更加可行，将创造一个更强大和可持续的粮食系统。SBIR第二阶段的工作将设计、建造和展示一个全尺寸的自动化温室农场原型。该原型将在几周内保持完全自主，不需要人类进入农场，而从种子到收获作物储存的所有过程都是机器人完成的。在任何价位上，都没有温室技术能够证明有能力实现这种程度的自动化。这项技术将通过解决受控环境农业系统目前面临的资本成本、劳动力和能源障碍，推动机器人技术在食品生产中的应用。主要挑战包括在没有任何人为干预的情况下每天生产约340个工厂，低成本的设置和持续运营设计，以及实时调整产品产量以满足市场需求的能力。通过高度的系统自动化，包括用于工厂检查和自清洁过程的计算机视觉，人类与生长过程的互动将受到限制。新的植物生长和处理过程将允许几乎任何类型的绿叶绿色或草本植物生长。各种传感器将用于监测条件和调整系统，使新鲜农产品在没有合适的农业机会的地区。该奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的知识价值和更广泛的影响审查标准。