Sponsor Agency: NSF-USDA-NRI
Karkee, M.*; Lewis, K.; Mo, Changki; Zhang, Q.
Harvest is the most labor-intensive operation in apple and pear orchards, requiring heavy utilization of seasonal labor. The development of robotic technology for harvesting tree fruit has achieved only limited success due to insufficient speed and accuracy of fruit recognition and removal. Lack of such technology is a crucial problem for the long-term sustainability of the domestic tree fruit industry because the cost of labor continues to increase and the availability of a semi-skilled labor force is becoming increasingly uncertain. The long-term goal of this work is to reduce dependency on human labor through mechanization and human-machine collaboration while increasing yields of premium quality fruit. The overall objective is to develop a framework for knowledge transfer and collaboration between human and machine. This objective will be achieved through the understanding of the dynamics of the hand picking of fruit, development of an effective end-effector based on the knowledge of hand picking, and a framework of hardware and software for optimal collaboration between human and machine for fruit detection. A trans-disciplinary team of experts is involved in this project, which is crucial for the successful completion of these activities. This project was initiated in fall 2013 and significant progress has been made in understanding fruit removal dynamics, fruit detection and development of end-effector and manipulator for robotic apple picking.