Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Robotics is the subjec t of a report. According to news originating from Beijing, People's Republic of China, by NewsRx correspondents, research stated, "The application of robotic gr asping for agricultural products pushes automation in agriculture-related indust ries. Cucumber, a common vegetable in greenhouses and supermarkets, often needs to be grasped from a cluttered scene." Financial support for this research came from Beijing Innovation Consortium of A griculture Research System. Our news journalists obtained a quote from the research from China Agricultural University, "In order to realize efficient grasping in cluttered scenes, a fully automatic cucumber recognition, grasping, and palletizing robot system was cons tructed in this paper. The system adopted Yolact++ deep learning network to segm ent cucumber instances. An early fusion method of F-RGBD was proposed, which inc reases the algorithm's discriminative ability for these appearance-similar cucum bers at different depths, and at different occlusion degrees. The results of the comparative experiment of the F-RGBD dataset and the common RGB dataset on Yola ct++ prove the positive effect of the F-RGBD fusion method. Its segmentation mas ks have higher quality, are more continuous, and are less false positive for pri oritizinggrasping prediction. Based on the segmentation result, a 4D grab line prediction method was proposed for cucumber grasping. And the cucumber detection experiment in cluttered scenarios is carried out in the real world."
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