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Active Pushing for Better Grasping in Dense Clutter with Deep Reinforcement Learning 会议论文
, Shanghai, China, 6-8 Nov. 2020
Authors:  Lu, Ning;  Lu, Tao;  Cai, Yinghao;  Wang, shuo
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基于深度强化学习与力封闭融合的三指手机器人抓取方法研究 学位论文
工程硕士, 中国科学院自动化研究所: 中国科学院大学, 2020
Authors:  刘永乐
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机器人抓取  深度强化学习  力封闭  域随机化  
基于深度强化学习的机器人抓取策略的研究 学位论文
工学硕士, 北京: 中国科学院自动化研究所, 2020
Authors:  陈斌
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深度强化学习,机器人自主抓取,多动作协同抓取  
A Grasping CNN with Image Segmentation for Mobile Manipulating Robot 会议论文
, Dali, China, 6-8 Dec. 2019
Authors:  Yu, Yingying;  Cao, Zhiqiang;  Liang, Shuang;  Liu, Zhicheng;  Yu, Junzhi;  Chen, Xuechao
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机器人操作目标的点云建模及位姿估计 学位论文
, 中国科学院自动化研究所: 中国科学院自动化研究所, 2019
Authors:  于灏
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机器人控制  目标识别  语义分割  点云配准  位姿估计  机器人抓取  
Flexible Robotic Grasping Strategy with Constrained Region in Environment 期刊论文
International Journal of Automation and Computing, 2017, 卷号: 14, 期号: 5, 页码: 552-563
Authors:  Chao Ma;  Hong Qiao;  Rui Li;  Xiao-Qing Li
Adobe PDF(1348Kb)  |  Favorite  |  View/Download:15/1  |  Submit date:2021/02/23
Grasping strategy  compliant grasping  dexterous robotic hands  attractive region in environment  constrained region in environment.  
Grasping Objects: The relationship between the cage and form-closure grasp 期刊论文
IEEE ROBOTICS & AUTOMATION MAGAZINE, 2017, 卷号: 24, 期号: 3, 页码: 82-94
Authors:  Su, Jianhua;  Hong,Qiao;  Liu,Chuankai;  Song,Yongbo;  Yang,Ailong;  Su,Jianhua
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Caging  Grasping  
The grasping point for planar workpiece based on fuzzy connectedness prior knowledge 会议论文
IEEE Robio2016, 中国青岛, 3-7 Dec. 2016
Authors:  Jingyi Zheng;  Li, En;  Liang, Zize
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Grasping Point  Planar Workpiece  Prior Knowledge  
基于视觉的铝电解槽机器人自主抓取作业的关键技术研究 学位论文
, 北京: 中国科学院研究生院, 2016
Authors:  郑晶怡
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铝电解槽  图像分割  自适应灰度差法  先验知识  避障路径规划  
The Concept of "Attractive Region in Environment" and its Application in High-Precision Tasks With Low-Precision Systems 期刊论文
IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2015, 卷号: 20, 期号: 5, 页码: 2311-2327
Authors:  Qiao, Hong;  Wang, Min;  Su, Jianhua;  Jia, Shengxin;  Li, Rui
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Assembly  Attractive Region In Environment (Arie)  Grasping  Localization  Sensorless Manipulation