An automated apple harvesting robot—From system design to field evaluation

Abstract Decreased availability and rising cost in labor poses a serious threat to the long‐term profitability and sustainability of the apple industry in the United States and many other countries. Harvest automation is thus urgently needed. In this paper, we present the unified system design and field evaluation of a new apple harvesting robot. The robot is mainly composed of a specially designed perception component, a four‐degree‐of‐freedom manipulator, an improved vacuum‐based soft end‐effector, and a dropping/catching component to receive and transport picked fruits. Software algorithms are developed to enable synergistic coordination of the hardware components for efficient, automated harvesting of apples in challenging orchard environments. Specifically, by integrating modified triangulation and image processing and analysis algorithms, a novel perception strategy is developed to achieve robust apple detection and precise localization. Improved planning and control algorithms are developed to guide the robot to the target positions. The performance of the robotic system was evaluated through field tests in two apple orchards with different tree architectures and foliage conditions. In the orchard where trees were young and well‐pruned, the robot achieved 82.4% successful harvesting rate. In a second, older orchard with dense, clustered branches and foliage, the robot had 65.2% successful rate. The average cycle time to harvest a fruit was approximately 6 s, which included software algorithm processing and hardware execution. Moreover, through an in‐depth analysis of the obtained results, limitations and planned future works are discussed.