Semantic Policy Network for Zero-Shot Object Goal Visual Navigation
文献类型：期刊论文
| 作者 | Zhao, Qianfan2,3; Zhang, Lu2,3 ; He, Bin1; Liu, Zhiyong2,3
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| 刊名 | IEEE ROBOTICS AND AUTOMATION LETTERS
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| 出版日期 | 2023-11-01 |
| 卷号 | 8期号:11页码:7655-7662 |
| ISSN号 | 2377-3766 |
| 关键词 | Deep learning path planning reinforcement learning vision-based navigation |
| DOI | 10.1109/LRA.2023.3320014 |
| 通讯作者 | Liu, Zhiyong(zhiyong.liu@ia.ac.cn) |
| 英文摘要 | The task of zero-shot object goal visual navigation (ZSON) aims to enable robots to locate previously "unseen" objects by visual observations. This task presents a significant challenge since the robot must transfer the navigation policy learned from "seen" objects to "unseen" objects through auxiliary semantic information without training samples, a process known as zero-shot learning. In order to address this challenge, we propose a novel approach termed the Semantic Policy Network (SPNet). The SPNet consists of two modules that are deeply integrated with semantic embeddings: the Semantic Actor Policy (SAP) module and the Semantic Trajectory (ST) module. The SAP module generates actor network weight bias based on semantic embeddings, creating unique navigation policies for different target classes. The ST module records the robot's actions, visual features, and semantic embeddings at each step, and aggregates information in both the spatial and temporal dimensions. To evaluate our approach, we conducted extensive experiments using MP3D dataset, HM3D dataset, and RoboTHOR. Experimental results indicate that the proposed method outperforms other ZSON methods for both seen and unseen target classes. |
| 资助项目 | National Key Research and Development Plan of China[2020AAA0108902] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100] ; NSFC[62206288] |
| WOS研究方向 | Robotics |
| 语种 | 英语 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| WOS记录号 | WOS:001085222400013 |
| 资助机构 | National Key Research and Development Plan of China ; Strategic Priority Research Program of Chinese Academy of Science ; NSFC |
| 源URL | [http://ir.ia.ac.cn/handle/173211/54289]  |
| 专题 | 多模态人工智能系统全国重点实验室 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 通讯作者 | Liu, Zhiyong |
| 作者单位 | 1.Tongji Univ, Coll Elect & Informat Engn, Shanghai 200070, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Multimodel Artificial Intelligence S, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Qianfan,Zhang, Lu,He, Bin,et al. Semantic Policy Network for Zero-Shot Object Goal Visual Navigation[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2023,8(11):7655-7662. |
| APA | Zhao, Qianfan,Zhang, Lu,He, Bin,&Liu, Zhiyong.(2023).Semantic Policy Network for Zero-Shot Object Goal Visual Navigation.IEEE ROBOTICS AND AUTOMATION LETTERS,8(11),7655-7662. |
| MLA | Zhao, Qianfan,et al."Semantic Policy Network for Zero-Shot Object Goal Visual Navigation".IEEE ROBOTICS AND AUTOMATION LETTERS 8.11(2023):7655-7662. |
入库方式： OAI收割
来源：自动化研究所
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