Can the challenges posed by increasing labor costs and a shortage in the skilled labor workforce be effectively addressed through innovative human-AI partnerships?
Can such partnerships augment and amplify worker skill, machine efficiency, and farm productivity?
To address these questions, the AgAID team is developing innovative and inclusive human-AI workflows at the human-machine interface in farm environments. These workflows will help improve the efficiency of farm robots while improving farm worker productivity and skill levels.
The research thrust will cover multiple use-cases at the human-machine interface to cover a broad spectrum of crop labor tasks that involve human-robot decision making.
Example use-cases include:
- Tree shaking used in mechanical harvesting of nut trees;
- Blossom thinning used in orchards to improve harvest quality; and
- Tree dormant pruning used in orchards to improve tree health.