SBIR-STTR Award

The broader impact/commercial potential of this project will address the ability to use automation to harvest strawberries in the United States in an environment where migrant labor is scarce and the work is undesirable. The project is borrowing techniques and methods that have been used and refined in many other high volume manufacturing/production industries and applying the applicable ideas to harvesting food crops with automated machines. Big data methods are also being developed in conjunction with the acquisition techniques that will assist crop growing with predictive information about future yields and help with monitoring plant health in relation to disease and pest infestation. The business model being developed helps the adoption of the technology into the farming community by not requiring the farmers to have large capital outlays by providing the anticipated machines to the farmers as a service to replace their labor. The initiation of the service will therefore be an easy decision for a farmer to make and will be helpful in establishing the standard for future harvesting models and techniques.This Small Business Innovation Research (SBIR) Phase I project is developing techniques and ideas to be able to accomplish the robotic harvesting of some of the most labor intensive and delicate fruit. Special machine vision techniques are being utilized to be able to simultaneously detect, decipher and target the fruit at a speeds conducive to commercial harvesting. Also, unique machine techniques that will enable the harvesting of the fruit without bruising. Objectives include experimenting with ideas that will lead to more consistent fruit packing and techniques to increase fruit shelf life after picking. Most prior research in these areas focused on being able to pick the fruit with machines and not so much on the ability to do it at commercial speeds. The entire purpose of the systems of the Harvest CROO is to rapidly acquire the fruit under the plants and then be able to pack and carry it out of the fields. Many of the projects until this point had no allotment for removing the fruit from the fields. The Harvest CROO system will establish standards for this.

The broader impact/commercial potential of this project includes development of berry post-picking screening and handling that will provide a safe and efficient way to remove contaminated berries from the processing stream of an automated harvester. The project will advance machine vision technology for robotic harvesting and will be a key enabling technology leading to acceptance of automated harvesting as safe and effective. The market sector addressed by this project is strawberry farmers, though the technology will be applicable to other types of fruit and vegetable farming as well. The automated harvesting technology advanced by this project will alleviate chronic and worsening labor shortages faced by strawberry farmers and will ensure that strawberries remain affordable and available to consumers. Filling the need created by farming labor shortages is a $1 billion business opportunity.This Small Business Innovation Research (SBIR) Phase II project will develop new vision processing and inspection methods vital to enabling use of an automated, robotic strawberry harvester. Acceptance of automated harvesting technology by strawberry farmers hinges on the ability of the harvester to remove bad berries from the plant without allowing the undesirable berries from entering the harvester packaging stream and potentially contaminating large quantities of berries. To achieve this, it will be necessary for the harvester to identify and eliminate diseased, rotten, damaged, or infested berries at multiple stages in the stream from automated picking to final packaging. The classification method that identifies the berries to be eliminated will be extremely accurate, with a very high detection rate and a low false alarm rate. The methods developed will be suitable for installation on a farming machine that is subject to a harsh outdoor environment as well as the shock and vibration environment found on a robotic harvesting device. New handling processes will be developed that will allow automated inspection of the entire berry without damaging the fruit or creating a risk of cross contamination from infected berries, significantly advancing the state of the art for automated strawberry processing.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.