A Strawberry Harvest-Aiding System with Crop-Transport Collaborative Robots: Design, Development, and Field Evaluation

Details

• Personal Author:
  Arikapudi R ; Fei Z ; Peng C ; Slaughter D ; Vougioukas S
• Description:
  Mechanizing the manual harvesting of fresh market fruits constitutes one of the biggest challenges to the sustainability of the fruit industry. During manual harvesting of some fresh-market crops like strawberries and table grapes, pickers spend significant amounts of time walking to carry full trays to a collection station at the edge of the field. A step toward increasing harvest automation for such crops is to deploy harvest-aid collaborative robots (co-bots) that transport empty and full trays, thus increasing harvest efficiency by reducing pickers' non-productive walking times. This study presents the development of a co-robotic harvest-aid system and its evaluation during commercial strawberry harvesting. At the heart of the system lies a predictive stochastic scheduling algorithm that minimizes the expected non-picking time, thus maximizing the harvest efficiency. During the evaluation experiments, the co-robots improved the mean harvesting efficiency by around 10% and reduced the mean non-productive time by 60%, when the robot-to-picker ratio was 1:3. The concepts developed in this study can be applied to robotic harvest-aids for other manually harvested crops that involve walking for crop transportation. [Description provided by NIOSH]
• Subjects:
  Agriculture Occupational Health Safety
• Keywords:
  Agricultural Processes Author Keywords: Agricultural Robotics Emerging Technology Equipment Design Equipment Testing Mobile Equipment Mobile Robots Optimization Robotics Systems Design
• ISSN:
  1556-4959
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  California ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  39
• Issue:
  8
• NIOSHTIC Number:
  nn:20067891
• Citation:
  J Field Robot 2022 Dec; 39(8):1231-1257
• Contact Point Address:
  Chen Peng, Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, USA
• Email:
  penchen@ucdavis.edu
• Federal Fiscal Year:
  2023
• NORA Priority Area:
  Agriculture, Forestry and Fishing
• Performing Organization:
  University of California - Davis
• Peer Reviewed:
  True
• Start Date:
  20010930
• Source Full Name:
  Journal of Field Robotics
• End Date:
  20270929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:3714e96615de176e1deebb1db96f5a0d7f3df403be9da5887205897eddd92b0a4d32f890f202080edd48b28b105c2e1a25f82724858cc6007a615bca6469d3a0
• Download URL:
  https://stacks.cdc.gov/view/cdc/230128/cdc_230128_DS1.pdf
• File Type:
  [PDF - 12.10 MB ]