Bimanual crop manipulation for human-inspired robotic harvesting

Most existing robotic harvesters utilize a unimanual approach; a single arm grasps the crop and detaches it, either via a detachment movement, or by cutting its stem with a specially designed gripper/cutter end-effector. However, such unimanual solutions cannot be applied for sensitive crops and cluttered environments like grapes and a vineyard where obstacles may occlude the stem and leave no space for the cutter's placement. In such cases, the solution would require a bimanual robot in order to visually unveil the stem and manipulate the grasped crop to create cutting affordances which is similar to the practice used by humans. In this work, a dual-arm coordinated motion control methodology for reaching a stem pre-cut state is proposed. The camera equipped arm with the cutter is reaching the stem, unveiling it as much as possible, while the second arm is moving the grasped crop towards the surrounding free-space to facilitate its stem cutting. Lab experimentation on a mock-up vine setup with a plastic grape cluster evaluates the proposed methodology, involving two UR5e robotic arms and a RealSense D415 camera.

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.