GraspFusionNet: a two-stage multi-parameter grasp detection network based on RGB–XYZ fusion in dense clutter von Wang, Weiming, Liu, Wenhai, Hu, Jie, Fang, Yi, Shao, Quanquan, Qi, Jin

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Object Detection-Based One-Shot Imitation Learning with an RGB-D Camera von Shao, Quanquan, Qi, Jin, Ma, Jin, Fang, Yi, Wang, Weiming, Hu, Jie

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Location Instruction-Based Motion Generation for Sequential Robotic Manipulation von Shao, Quanquan, Hu, Jie, Wang, Weiming, Fang, Yi, Xue, Teng, Qi, Jin

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Composable Instructions and Prospection Guided Visuomotor Control for Robotic Manipulation von Shao, Quanquan, Hu, Jie, Wang, Weiming, Fang, Yi, Han, Mingshuo, Qi, Jin, Ma, Jin

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Smooth and time-optimal S-curve trajectory planning for automated robots and machines von Fang, Yi, Hu, Jie, Liu, Wenhai, Shao, Quanquan, Qi, Jin, Peng, Yinghong

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Target Pose Guided Whole-body Grasping Motion Generation for Digital Humans von Shao, Quanquan, Fang, Yi

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Research on Spatially Adaptive High-Order Total Variation Model for Weak Fluorescence Image Restoration von Ma, Jin, Xue, Teng, Shao, Quanquan, Hu, Jie, Wang, Weiming

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Target Pose Guided Whole-body Grasping Motion Generation for Digital Humans von Shao, Quanquan, Fang, Yi

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Combining RGB and Points to Predict Grasping Region for Robotic Bin-Picking von Shao, Quanquan, Hu, Jie

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Combining RGB and Points to Predict Grasping Region for Robotic Bin-Picking von Shao, Quanquan, Hu, Jie

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Object-Agnostic Suction Grasp Affordance Detection in Dense Cluster Using Self-Supervised Learning.docx von Han, Mingshuo, Liu, Wenhai, Pan, Zhenyu, Xue, Teng, Shao, Quanquan, Ma, Jin, Wang, Weiming

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Bayesian Grasp: Robotic visual stable grasp based on prior tactile knowledge von Xue, Teng, Liu, Wenhai, Han, Mingshuo, Pan, Zhenyu, Ma, Jin, Shao, Quanquan, Wang, Weiming

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Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter von Shao, Quanquan, Hu, Jie, Wang, Weiming, Fang, Yi, Liu, Wenhai, Qi, Jin, Ma, Jin

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Method and system for generating grabbing posture of dexterous hand guided by limited grabable area von SHAO QUANQUAN, FANG YI

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Bayesian Grasp: Robotic visual stable grasp based on prior tactile knowledge von Teng Xue, Liu, Wenhai, Han, Mingshuo, Pan, Zhenyu, Ma, Jin, Shao, Quanquan, Wang, Weiming

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Object-Agnostic Suction Grasp Affordance Detection in Dense Cluster Using Self-Supervised Learning.docx von Han, Mingshuo, Liu, Wenhai, Pan, Zhenyu, Teng Xue, Shao, Quanquan, Ma, Jin, Wang, Weiming

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Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter von Shao, Quanquan, Hu, Jie, Wang, Weiming, Fang, Yi, Liu, Wenhai, Jin, Qi, Ma, Jin

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Image annotation model training method and device, electronic equipment and storage medium von SHAO QUANQUAN, BIE XIAOFANG, ZHANG SONG, WANG HANCHAO, ZHU LU, YAN WEI

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Intelligent robot track monitoring system and method based on cloud computing von SHAO QUANQUAN, GUAN XINPING, ZHAO YUDI, FANG YI, GU CHAOCHEN, WU LINGMI

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Industrial robot dynamic management system and method based on big data von SHAO QUANQUAN, GUAN XINPING, ZHAO YUDI, MA JIN, FANG YI, GU CHAOCHEN, WU LINGMI

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