Optimized predictive dispatching of Robotic Harvest-Aids using Multiple Scenario Approach
Date:
A small team of harvest-aiding mobile robots (FRAIL-bots) is being designed to aid large teams of human pickers in commercial strawberry harvesting by providing them with empty containers and transporting containers filled with harvested crops to collection stations at the edge of a field. The collective operation of these robots can serve requests for point-to-point transport in real time. The goal is to improve pickers’ job cycle by dramatically reducing non-productive walking and unloading times. To do so, individual FRAIL-bots with limited amounts must be dispatched and routed dynamically, in order to optimally match the dynamic and stochastic spatiotemporal distribution of real-time transport requests and resolve any spatial and resource sharing conflicts in the field correspondingly.
