Click on “Download PDF” for the PDF version or on the title for the HTML version. If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options. Research Progress of Automated Seedling Transplanter in GreenhousePublished by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org Citation: 2015 ASABE Annual International Meeting 152155561_.(doi:10.13031/aim.20152155561)Authors: Junhua Tong, Huanyu Jiang, Chuanyu Wu, Gaohong Yu, Zhuohua Jiang Keywords: Automated transplanter, Seedling, End-effector, Leaf area, Path optimization. Abstract. Transplanting healthy seedlings from high density to low-density trays for further growth, and replacing bad or missing plants with healthy ones are important tasks for seedlings cultivation in plug tray in greenhouse. Developing automated seedling transplanter to take the place of labor to do these repetion and heavy tasks are meaningful. Research progresses which include four dimensions key technology of automated transplanter are presented in this paper. They are suitable seedling plug states for mechanical transplanting, end-effector design and testing, methods for seedling quality evaluation based on machine vision techniques, and seedling transplanting path optimization. Five parameters which include clamping needle angle, gripper needles, plug moisture content, taproot length, and bulk material proportion were tested separately to demonstrate the affection for plug compressive resistance. A plugging and clamping end-effector with two cylinder drivers was developed and tested with more than 95.8% success rate. Leaf area calculation methods were developed to evaluate seedling quality based on machine vision technology. Leaves overlapping problem was solved with more than 98.6% identification accuracy for vegetable seedling. Genetic algorithm was introduced into the transplanting path optimization. And the length has been shortened 8.5% and 3.7 m for transplanting fifty seedlings which compared with fixed sequential method. This knowledge is useful for developing automated seedling transplanter with effective end-effector, seedling detection, and transplanting strategy. (Download PDF) (Export to EndNotes)
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