  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 the empty and full trays, thus increasing harvest
efficiency by reducing pickers' non-productive walking times. This work
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 work can be applied to robotic
harvest-aids for other manually harvested crops that involve walking for crop
transportation.
