Researchers at the University of California, Davis have developed an automated harvesting system using predictive scheduling for crop-transport robots, reducing manual labor, and increasing harvesting efficiency.
The technology is designed for more efficient fruit harvesting. It is composed of mobile robots, instrumented carts, and a predictive scheduling server. The mobile robot system transports filled harvesting containers from pickers on the field to collection stations, while providing pickers with new empty containers. Pickers' container needs are predicted by the scheduling server, which optimizes coordination of the robot fleet. The carts send real-time location and harvested crop weight data to a field computer. The system increases harvesting efficiency by reducing pickers' non-productive walking times.
labor, harvest, collaborative robots, transport, scheduling