ZTE Corporation＇s next-generation xPON optical access platform has won the InfoVision Green Broadband Award at Broadband World Forum Europe （BBWF Europe） 2010 held in Paris, France. This is the second time a ZTE FT...ZTE Corporation＇s next-generation xPON optical access platform has won the InfoVision Green Broadband Award at Broadband World Forum Europe （BBWF Europe） 2010 held in Paris, France. This is the second time a ZTE FTTx product has won an Infovision award at this prestigious telecommunications industry event, following a win in 2007.展开更多
[提示]文章虽短,却动人心魄,开人眼界!人在水中遇到鲨鱼,如在山中遇到猛 虎。而这位被人称为the Iceman(能否译成"冰汉"?)却徒手将一条对他手下的人构成生命威胁的鲨鱼拖上岸,并用刀将鲨鱼杀死!其猛其勇,堪与当年武松媲美!文...[提示]文章虽短,却动人心魄,开人眼界!人在水中遇到鲨鱼,如在山中遇到猛 虎。而这位被人称为the Iceman(能否译成"冰汉"?)却徒手将一条对他手下的人构成生命威胁的鲨鱼拖上岸,并用刀将鲨鱼杀死!其猛其勇,堪与当年武松媲美!文章中的两句连续使用了4个动词,极为精彩:Captain Sigurdur Petursson,known to locals as"the Iceman,"ran into the shallow water and grabbed theshark by its tail.He dragged it off to dry land and killed it with his knife.展开更多
In present-day industrial settings,where robot arms performtasks in an unstructured environment,theremay exist numerousobjects of various shapes scattered in randompositions,making it challenging for a robot armtoprec...In present-day industrial settings,where robot arms performtasks in an unstructured environment,theremay exist numerousobjects of various shapes scattered in randompositions,making it challenging for a robot armtoprecisely attain the ideal pose to grasp the object.To solve this problem,a multistage robotic arm flexible grasp detection method based on deep learning is proposed.This method first improves the Faster RCNN target detection model,which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes.Then,a Squeeze-and-Excitation module is introduced to design a multitarget grasping pose generation network based on a deep convolutional neural network to generate a variety of graspable poses for grasped objects.Finally,a multiobjective IOU mixed area attitude evaluation algorithm is constructed to screen out the optimal grasping area of the grasped object and obtain the optimal grasping posture of the robotic arm.The experimental results show that the accuracy of the target detection network improved by the method proposed in this paper reaches 96.6%,the grasping frame accuracy of the grasping pose generation network reaches 94%and the flexible grasping task of the robotic arm in an unstructured scene in a real environment can be efficiently and accurately implemented.展开更多
为从不同角度识别目标物体以及解决左右两幅图像中目标轮廓中心不匹配的问题,将SURF(Speeded Up Robust Features)算法与Grab Cut算法相结合,离线采集目标物体不同角度的图像,生成目标模板图片库。利用SURF算法完成目标物体的识别;利用S...为从不同角度识别目标物体以及解决左右两幅图像中目标轮廓中心不匹配的问题,将SURF(Speeded Up Robust Features)算法与Grab Cut算法相结合,离线采集目标物体不同角度的图像,生成目标模板图片库。利用SURF算法完成目标物体的识别;利用SURF算法自动初始化Grab Cut算法,实现目标轮廓的提取;利用基于灰度相关的区域匹配算法完成目标轮廓中心点的匹配,结合三维重建原理实现目标定位。实验结果表明,该方法可以成功识别目标物体并对目标物体进行准确定位。展开更多
文摘ZTE Corporation＇s next-generation xPON optical access platform has won the InfoVision Green Broadband Award at Broadband World Forum Europe （BBWF Europe） 2010 held in Paris, France. This is the second time a ZTE FTTx product has won an Infovision award at this prestigious telecommunications industry event, following a win in 2007.
文摘[提示]文章虽短,却动人心魄,开人眼界!人在水中遇到鲨鱼,如在山中遇到猛 虎。而这位被人称为the Iceman(能否译成"冰汉"?)却徒手将一条对他手下的人构成生命威胁的鲨鱼拖上岸,并用刀将鲨鱼杀死!其猛其勇,堪与当年武松媲美!文章中的两句连续使用了4个动词,极为精彩:Captain Sigurdur Petursson,known to locals as"the Iceman,"ran into the shallow water and grabbed theshark by its tail.He dragged it off to dry land and killed it with his knife.
基金supported in part by the National Natural Science Foundation of China(No.52165063)Guizhou Provincial Science and Technology Projects(Qiankehepingtai-GCC[2022]006-1,Qiankehezhicheng[2021]172,[2021]397,[2021]445,[2022]008,[2022]165)+1 种基金Natural Science Research Project of Guizhou Provincial Department of Education(Qianjiaoji[2022]No.436)Guizhou Province Graduate Research Fund(YJSCXJH[2021]068).
文摘In present-day industrial settings,where robot arms performtasks in an unstructured environment,theremay exist numerousobjects of various shapes scattered in randompositions,making it challenging for a robot armtoprecisely attain the ideal pose to grasp the object.To solve this problem,a multistage robotic arm flexible grasp detection method based on deep learning is proposed.This method first improves the Faster RCNN target detection model,which significantly improves the detection ability of the model for multiscale grasped objects in unstructured scenes.Then,a Squeeze-and-Excitation module is introduced to design a multitarget grasping pose generation network based on a deep convolutional neural network to generate a variety of graspable poses for grasped objects.Finally,a multiobjective IOU mixed area attitude evaluation algorithm is constructed to screen out the optimal grasping area of the grasped object and obtain the optimal grasping posture of the robotic arm.The experimental results show that the accuracy of the target detection network improved by the method proposed in this paper reaches 96.6%,the grasping frame accuracy of the grasping pose generation network reaches 94%and the flexible grasping task of the robotic arm in an unstructured scene in a real environment can be efficiently and accurately implemented.
