Knowledge Commons of Institute of Automation,CAS
A Real 3D Embodied Dataset for Robotic Active Visual Learning | |
Zhao, Qianfan1,2; Zhang, Lu1,2; Wu, Lingxi2,4; Qiao, Hong1,2; Liu, Zhiyong1,2,3 | |
发表期刊 | IEEE ROBOTICS AND AUTOMATION LETTERS |
ISSN | 2377-3766 |
2022-07-01 | |
卷号 | 7期号:3页码:6646-6652 |
通讯作者 | Liu, Zhiyong(zhiyong.liu@ia.ac.cn) |
摘要 | Active interaction with environments is one of the striking characteristics of robotic active vision, which allows robots to move to facilitate visual tasks. Recently, several embodied AI platforms have been proposed as the synthetic environments to study robotic active vision, without needing to interact in real world. However, by using synthetic data, model trained on these platforms will suffer performance degradation when applied in reality. In this letter, a real 3D embodied dataset is proposed for robotic active visual learning. The proposed dataset consists of real point cloud data densely collected in 7 real-world indoor scenes. In our embodied dataset, researchers are able to simulate the movements and interactions of robots in indoor environments and obtain real visual data, which will not lead to performance degradation in reality. Furthermore, we proposed a 3D divergency policy that can guide robots to move and collect data to improve visual performance in novel environments. The proposed policy is designed following a simple fact: a good 3D detector should produce consistent 3D detection results for the same object from different viewpoints. Therefore, our policy encourages the robot to explore the area where the detector generates different 3D bounding boxes for the same object and helps the robot improve its visual performance in novel scenes. |
关键词 | Data sets for robotic vision deep learning for visual perception reinforcement learning |
DOI | 10.1109/LRA.2022.3157028 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Plan of China[2020AAA0108902] ; Strategic Priority Research Program of ChineseAcademy of Science[XDB32050100] ; NSFC, China[61627808] ; NSFC, China[2019622101001] |
项目资助者 | National Key Research and Development Plan of China ; Strategic Priority Research Program of ChineseAcademy of Science ; NSFC, China |
WOS研究方向 | Robotics |
WOS类目 | Robotics |
WOS记录号 | WOS:000805161600004 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49564 |
专题 | 多模态人工智能系统全国重点实验室_机器人理论与应用 |
通讯作者 | Liu, Zhiyong |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 4.Univ Calif Santa Barbara, Dept Math, Coll Letters & Sci, Santa Barbara, CA 93106 USA |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhao, Qianfan,Zhang, Lu,Wu, Lingxi,et al. A Real 3D Embodied Dataset for Robotic Active Visual Learning[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2022,7(3):6646-6652. |
APA | Zhao, Qianfan,Zhang, Lu,Wu, Lingxi,Qiao, Hong,&Liu, Zhiyong.(2022).A Real 3D Embodied Dataset for Robotic Active Visual Learning.IEEE ROBOTICS AND AUTOMATION LETTERS,7(3),6646-6652. |
MLA | Zhao, Qianfan,et al."A Real 3D Embodied Dataset for Robotic Active Visual Learning".IEEE ROBOTICS AND AUTOMATION LETTERS 7.3(2022):6646-6652. |
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