SBIR Phase I:Development of a Multi-Robot System to Reduce End-to-End Labor Automation Costs in Local Food Production

该SBIR一期项目的更广泛影响/商业潜力在于，通过城市农业中端到端劳动力自动化和能源管理的新方法，为社会各阶层提供更多健康、本地和负担得起的农产品。通过低足迹的垂直温室设计，这项技术将使个人能够在一小块可用空间上为他们的社区种植农产品。这种农产品将成为大规模工业化农业和外国进口食品的一个有吸引力的替代品，不仅是出于可持续性方面的考虑，而且由于其优越的新鲜度、质量和味道。该项目将对提高当地农业技术产生影响，以进一步提高城市社区商业粮食生产的可行性。创建一个经济上可行的城市农场将对美国的食品系统和环境产生持久的影响，因为它将为可持续的食品生产提供一种手段。第一阶段的工作将用于设计、建造和演示一个次级垂直农场原型，该原型将展示农场端到端劳动力自动化各个方面的成本效益方法。这将通过解决当地控制的环境农业系统目前面临的劳动力和能源障碍，推动机器人在食品生产中的实施。为了实现这一目标，主要的挑战包括：(1)自动化，在较长时间内完全消除人工劳动，(2)低成本设计的设置和正在进行的操作，以及(3)实时调整产品输出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产品。各种传感器被用来仔细监测条件和调整系统，允许在没有合适农业机会的地区生产新鲜农产品。在第一阶段开发的原型机器人农业系统将展示扩展城市农业所必需的端到端劳动自动化和能源管理技术。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this SBIR Phase I project lie in the greater availability of healthy, local, and affordable produce for all levels of society through new methods of end-to-end labor automation and energy management in urban agriculture. Through a low-footprint vertical greenhouse design, this technology will enable individuals to grow produce on small areas of available space for their community. The produce will be an attractive alternative to large-scale industrial agriculture and foreign food imports, not only for sustainability concerns, but through its superior freshness, quality, and taste. This project will have an impact on the advancement of local farming technologies to further the viability of commercial food production in urban communities. Creating an economically viable urban farm will have lasting impacts on the U.S. food system and environment as it will provide a means for sustainable food production.The Phase I effort will be used to design, build, and demonstrate a subscale vertical farm prototype that demonstrates cost-effective methods for all aspects of the farm’s end-to-end labor automation. This will advance the implementation of robotics in food production by addressing the labor and energy barriers that local controlled environmental agriculture systems currently face. To achieve this objective, key challenges include (1) automation to completely remove human labor over extended durations, (2) low-cost design for setup and ongoing operations, and (3) the ability to adjust product outputs in real-time to market demands. Human interaction with the grow process will be limited through 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 produce. A variety of sensors are used to carefully monitor conditions and adjust the system, allowing fresh produce in areas without suitable agricultural opportunities. The prototype robotic farming system being developed in the Phase I effort will demonstrate the end-to-end labor automation and energy management technologies necessary to the expansion of urban agriculture.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.