CCRI: Planning-C: A Framework for Development of Robots and IoT for Precision Agriculture

Agriculture is one of the least digitized industries. The US can gain a drastic advantage in this field by adopting automation for agriculture. Precision agriculture consists of using robotics and automation to increase economic benefits.

Automation using robots and Internet of Things is a key enabling factor for precision agriculture and can cut down greenhouse gas emissions and minimize impact on soil, water, and air. Robotic technologies can save tens of billions of dollars every year in herbicide, pesticide, fertilizer, and irrigation costs. They can eliminate the use of billions of pounds of chemicals that are harmful to the ecosystem.

In this project, a team of researchers from California, North Dakota, Texas, and New Hampshire, will plan and design a computer modeling software for robots and Internet of Things for precision agriculture. This software will enable scientists and engineers to deploy and test new robots and devices virtually in a computer without physically building them.

Using this award, the project team will collect a large amount of data (e.g., videos and images) from real-world farms and use this data to plan the aforementioned software. This data and open-source pedagogical tools will be made available to the public on the internet.

The fourth industrial revolution - characterized by smart automation and inter-connectivity - is about to change farm management practices forever. To hasten this positive change, the project team envisions an infrastructure that enables rapid development of robotic hardware, sensing technologies, software tools, and machine learning algorithms. While computer scientists and roboticists are developing novel software and hardware every day with great potential for precision agriculture, these tools typically fall short of real-world application.

The envisioned simulation environment for testing such tools will bridge the gap between fundamental research and real-world deployment. These tools can enable autonomous farm management, including precision weed/pest management, precision irrigation, autonomous crop health monitoring, and precision crop protection. This can dramatically cut down labor costs, reduce chemical usage, lower the impact on water resources, conserve the fertility of soil, and increase the yield of crops.

Computer scientists and roboticists will be able to get familiar with real-world challenges of precision agriculture, e.g., dramatic effects of precipitation on agriculture. The project team will collect preliminary data to prototype the infrastructure, organize workshops with interested researchers to plan the infrastructure, and connect with farmers and agronomists to gather feedback.

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.