Most target grabbing problems have been dealt with by computer vision system, however, computer vision method is not always enough when it comes to the precision contact grabbing problems during the teleoperation proc...Most target grabbing problems have been dealt with by computer vision system, however, computer vision method is not always enough when it comes to the precision contact grabbing problems during the teleoperation process, and need to be combined with the stiffness display to provide more effective information to the operator on the remote side. Therefore, in this paper a more portable stiffness display device with a small volume and extended function is developed based on our previous work. A new static load calibration of the improved stiffness display device is performed to detect its accuracy, and the relationship between the stiffness and the position is given. An effective target grabbing strategy is presented to help operator on the remote side to judge and control and the target is classified by multi-class SVM(supporter vector machine). The teleoperation system is established to test and verify the feasibility. A special experiment is designed and the results demonstrate that the improved stiffness display device could greatly help operator on the remote side control the telerobot to grab target and the target grabbing strategy is effective.展开更多
In the last two decades, the global interest on farmland grew at a remarkable pace. As a consequence, million hectares of land exchanged hands. The ways the transfers happened combined with their geographic concentrat...In the last two decades, the global interest on farmland grew at a remarkable pace. As a consequence, million hectares of land exchanged hands. The ways the transfers happened combined with their geographic concentration in Sub-Saharian Africa, have earned the phenomenon the name of ＂land grab＂. The agricultural sector considered a ＂sunset industry＂ when commodities prices were declining, is now attractive to financial investors. These foreign investments may be good as they may improve agricultural productivity or instead bad as they may benefit only financial investors. Some results in terms of environmental and local communities＇ worsening conditions have already emerged. This paper aims to investigate what drives the big size transfers of land, to empirically estimate their effects in terms of local employment and to assess the environmental effects produced by the rapid transformation in the use of vast amount of land in terms of CO2 emissions. It is also proposed to use the estimation in terms of local employment impact as a way of distinguishing between foreign direct investment and land grabbing.展开更多
Approved by Ministry of Culture in 1999 as China Wuqiao International Acrobatic Art Training Center, Hebei Wuqiao Acrobatic Art School started to train 6 students from Tanzania.
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
基金partially supported by the National Natural Science Foundation of China(61663027,61325018,81501560)the Science and Technology Department of Jiangxi Province of China(20151BAB207050)
文摘Most target grabbing problems have been dealt with by computer vision system, however, computer vision method is not always enough when it comes to the precision contact grabbing problems during the teleoperation process, and need to be combined with the stiffness display to provide more effective information to the operator on the remote side. Therefore, in this paper a more portable stiffness display device with a small volume and extended function is developed based on our previous work. A new static load calibration of the improved stiffness display device is performed to detect its accuracy, and the relationship between the stiffness and the position is given. An effective target grabbing strategy is presented to help operator on the remote side to judge and control and the target is classified by multi-class SVM(supporter vector machine). The teleoperation system is established to test and verify the feasibility. A special experiment is designed and the results demonstrate that the improved stiffness display device could greatly help operator on the remote side control the telerobot to grab target and the target grabbing strategy is effective.
文摘In the last two decades, the global interest on farmland grew at a remarkable pace. As a consequence, million hectares of land exchanged hands. The ways the transfers happened combined with their geographic concentration in Sub-Saharian Africa, have earned the phenomenon the name of ＂land grab＂. The agricultural sector considered a ＂sunset industry＂ when commodities prices were declining, is now attractive to financial investors. These foreign investments may be good as they may improve agricultural productivity or instead bad as they may benefit only financial investors. Some results in terms of environmental and local communities＇ worsening conditions have already emerged. This paper aims to investigate what drives the big size transfers of land, to empirically estimate their effects in terms of local employment and to assess the environmental effects produced by the rapid transformation in the use of vast amount of land in terms of CO2 emissions. It is also proposed to use the estimation in terms of local employment impact as a way of distinguishing between foreign direct investment and land grabbing.
文摘Approved by Ministry of Culture in 1999 as China Wuqiao International Acrobatic Art Training Center, Hebei Wuqiao Acrobatic Art School started to train 6 students from Tanzania.
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.
