Abstract
This paper reviews the state of the art and future perspective of greenhouse mechanization. Driving forces for mechanization are identified. Dutch greenhouse crop production is used as an example. Analysis of a generic crop production process combined with a review of the state of the art in greenhouse mechanization revealed that the first phases of plant production such as seeding, cutting, grafting and transplanting as well as the final phase of crop production including sorting and packing the harvested produce are mechanised. Those tasks do not require much human intelligence and/or fast and accurate eye-hand coordination. The available machines are largely based on principles of industrial automation consisting of mechanical solutions with only a limited amount of sensors and `intelligence? used. The next ten years, the available line of machines will be redesigned, extended and optimised. The middle phase of crop production including crop maintenance and harvest does not show much automation yet. Maintaining the crop and harvesting do rely on human intelligence and ability and are much more difficult to automate. The next ten years will show the advent of the next generation machines that will be based on the principles of mechatronics and robotics, combining smart mechanical design with sensors and `artificial intelligence? to achieve the fast and accurate eye-hand coordination needed for these difficult tasks. This trend is supported by the commercial development of a strawberry harvester in Japan and a rose harvesting robot and tomato de-leafing robot in the Netherlands. It is concluded that the slow progress in the field of robotic harvesting is to a large extent due to uncertainty in the working environment of the robot as a result of biological variability and the typical structure of the growing systems used. Progress in the field of greenhouse robotics therefore will not only rely on innovations in the field of robot technology but also on necessary innovations in the field of growing systems and plant breeding to reduce variability and thus to simplify the task
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