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一种协作型机械臂的动态轨迹规划方法 专利
专利类型: 发明, 专利号: CN112975939A, 公开日期: 2021-06-18,
Inventors:  于海斌;  王洪光;  姜勇
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一种基于零空间的机械臂速度层轨迹规划方法 专利
专利类型: 发明, 专利号: CN112975938A, 公开日期: 2021-06-18,
Inventors:  姜勇;  王洪光;  侯赵磊
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机械臂在复杂环境下的快速分割方法 专利
专利类型: 发明, 专利号: CN112991356A, 公开日期: 2021-06-18,
Inventors:  姜勇;  王洪光;  侯赵磊
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一种引入弹性变形的机械臂标定方法 专利
专利类型: 发明, 专利号: CN112959354A, 公开日期: 2021-06-15,
Inventors:  潘新安;  王洪光;  姜勇;  胡明伟;  王争;  宋屹峰
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一种融入注意力和预测的特征选择SLAM算法 期刊论文
智能系统学报, 2021, 卷号: 16, 期号: 6, 页码: 1039-1044
Authors:  曾毓菁;  姜勇
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即时定位与地图创建  视觉  注意力  预测  特征选择  logdet度量  延迟求值  贪婪算法  信息矩阵  
Feature selection SLAM algorithm incorporating attention and anticipation 会议论文
2021 IEEE 11th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021, Jiaxing, China, July 27-31, 2021
Authors:  Zeng YJ(曾毓菁);  Jiang Y(姜勇)
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Recognition of insulator based on yolov5 algorithm 会议论文
2021 IEEE 11th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021, Jiaxing, China, July 27-31, 2021
Authors:  Feng H(冯晗);  Jiang Y(姜勇)
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PatchCNN: An Explicit Convolution Operator for Point Clouds Perception 期刊论文
IEEE Geoscience and Remote Sensing Letters, 2021, 卷号: 18, 期号: 4, 页码: 726-730
Authors:  Wang F(王斐);  Zhang, Xing;  Jiang Y(姜勇);  Kong, Li;  Wei, Xiaotong
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Deep learning  explicit convolution  geometric relationship  point cloud perception  
基于虚拟力引导的人机协同目标抓取方法 期刊论文
智能系统学报, 2021, 卷号: 16, 期号: 4, 页码: 683-689
Authors:  姜通维;  姜勇
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虚拟力引导  力反馈  运动约束  机械臂避障  目标抓取  主从控制  遥操作  人机协同  
Geometric model-based joint angle selection criterion for force parameter identification Decoupling control method of position and posture in shaft-hole assembly 会议论文
2021 IEEE 11th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2021, Jiaxing, China, July 27-31, 2021
Authors:  Wang JH(王竣禾);  Jiang Y(姜勇);  (1,2) Lin S(林松)(1,2,3);  Kong FX(孔繁旭)
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compliance control  force feedback damping control  Parameter identification  Posture adjustment  Sample selection criterion  shaft - hole assembly