Automation for Specialty Crops: A Comprehensive Strategy, Current Results, and Future Goals

Sanjiv Singh1, Tara Baugher2 , Marcel Bergerman1 , Ben Grocholsky1, Jay Harper2 , Gwen-Alyn
Hoheisel3 , Larry Hull2 , Vincent Jones3 , George Kantor1, Harvey Koselka4, Karen Lewis3 , William
Messner1 , Henry Ngugi2, James Owen Jr.5 , Johnny Park6 , Clark Seavert5
1Carnegie
Mellon University, 2Penn State University, 3Washington State University,
4Vision Robotics, 5Oregon State University, 6Purdue University
Autonomous Prime Mover
Applications
Core Capabilities
Insect
Monitoring
Specialty crops constitute a $45 billion/year industry characterized by the need for
intensive cultivation. Specialty crops are facing a crisis of increasing labor costs and
shortages of available labor. In addition, an increasing consumer demand for a safe,
affordable, traceable, and high quality food supply, and the need to minimize the
environmental footprint represent key challenges for specialty crop sustainability in the
United States. Recently, our team started a four-year effort to develop a
comprehensive automation strategy for tree fruit production. Our approach is based on
a triad that spans the entire production spectrum, from the nursery tree stage to
harvest:
•  Information, mobility, and manipulation technologies, including reconfigurable
mobility, accurate positioning, information management and decision making, and
augmented fruit harvesting.
•  Plant science technologies, including detection of plant stress and disease,
monitoring of insect populations and infestation, automated caliper measurement,
and autonomous crop load scouting.
•  Socio-economic analyses, outreach/extension, and commercialization.
This four-year project is aimed at developing a comprehensive automation strategy for
specialty crops, with an initial focus on apples and nursery trees. While our preliminary
Year 1 results show that it is possible to develop technologies to increase farm
efficiency, reduce labor costs, and increase fruit quality, our (and others’) greatest
challenges will be to prove these technologies’ economic feasibility and overcome any
barriers to adoption.
Weed Detection and
Management
Plant Stress and
Disease Detection
Crop Load
Scouting
Caliper
Measurement
Augmented Fruit
Harvesting