A Survey of Robotic Harvesting Systems and Enabling Technologies

This paper presents a comprehensive review of ground agricultural robotic systems and applications with special focus on harvesting that span research and commercial products and results, as well as their enabling technologies. The majority of literature concerns the development of crop detection, field navigation via vision and their related challenges. Health monitoring, yield estimation, water status inspection, seed planting and weed removal are frequently encountered tasks. Regarding robotic harvesting, apples, strawberries, tomatoes and sweet peppers are mainly the crops considered in publications, research projects and commercial products. The reported harvesting agricultural robotic solutions, typically consist of a mobile platform, a single robotic arm/manipulator and various navigation/vision systems. This paper reviews reported development of specific functionalities and hardware, typically required by an operating agricultural robot harvester; they include (a) vision systems, (b) motion planning/navigation methodologies (for the robotic platform and/or arm), (c) Human-Robot-Interaction (HRI) strategies with 3D visualization, (d) system operation planning & grasping strategies and (e) robotic end-effector/gripper design. Clearly, automated agriculture and specifically autonomous harvesting via robotic systems is a research area that remains wide open, offering several challenges where new contributions can be made.

Automated summary

This paper provides a comprehensive review of ground agricultural robotic systems and their applications in harvesting. It focuses on the development of crop detection, field navigation, and related challenges. Tasks such as health monitoring, yield estimation, water status inspection, seed planting, and weed removal are common in this field. Robotic harvesting mainly targets apples, strawberries, tomatoes, and sweet peppers. The paper reviews the development of specific functionalities and hardware required by robotic harvesters, including vision systems, motion planning/navigation methodologies, HRI strategies, system operation planning & grasping strategies, and robotic end-effector/gripper design. The research area of automated agriculture and autonomous harvesting via robotic systems offers several challenges and opportunities for new contributions.