检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:韩冬[1,2,3] 黄攀峰[1,2] 齐志刚[1,2] HAN Dong;HUANG Panfeng;QI Zhigang(Research Center of Intelligent Robotics,Northwestern Polytechnical University,Xi’an 710072,China;National Key Laboratory of Aerospace Flight Dynamics,Northwestern Polytechnical University,Xi’an 710072,China;School of Physics and Information Engineering,Shanxi Normal University,Linfen 041000,China)
机构地区:[1]西北工业大学航天学院智能机器人研究中心,西安710072 [2]西北工业大学航天飞行动力学技术重点实验室,西安710072 [3]山西师范大学物理与信息工程学院,临汾041000
出 处:《载人航天》2019年第5期586-593,共8页Manned Spaceflight
基 金:载人航天预先研究项目(2018KC020081)
摘 要:针对局部自主遥操作过程中识别目标准确率低的问题,提出了一种基于改进快速区域卷积神经网络的抓取构型识别方法,通过对其区域生成网络中锚点尺度、前景特征区域、候选框的线性回归和分类网络分别进行改进,以提高抓取构型识别的准确率。首先将抓取构型参数化,然后在目标区域中利用锚点法对抓取构型参数进行识别,结合视觉传感器采集到的深度信息确定目标高度,并通过线性回归方法对抓取区域进行修正。通过搭建机器人试验平台,利用Cornell Grasp Dataset进行训练与测试进行验证。试验结果表明,提出的方法在简单网络识别准确率为96.4%,并成功实现机器人对目标的抓取。Based on improved faster regional convolutional neural network(faster R-CNN),an object detection and grasp configuration reorganization method was proposed to solve the problem of low accuracy in local autonomy teleoperation.The anchor scale of the regional proposal network,the foreground feature area,the candidate box linear regression and the classification network were improved to increase the accuracy of the grasp configuration recognition.First,the grasp configuration was parameterized by the algorithm.Then the anchor method was used to identify the grasp configuration parameters in the target area,and the depth information collected by the vision was incorporated to determine the object height.Through the linear regression method,the grasping area was corrected to make the grasp configuration parameter identification more precise,and the success rate of the capture was improved.In addition,a robot experiment platform was built and the network was trained and tested using the Cornell Grasp Dataset data set.The results showed that the proposed method achieved 96.4%accuracy in a simple network,and successful grasp of target by the robot was achieved.
关 键 词:局部自主遥操作 目标检测 抓取构型识别 快速区域卷积神经网络
分 类 号:V224.2[航空宇航科学与技术—飞行器设计]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:18.217.160.127