Ontology based autonomous robot task processing framework
文献类型：期刊论文
| 作者 | Ge, Yueguang1,2 ; Zhang, Shaolin1; Cai, Yinghao1; Lu, Tao1; Wang, Haitao1,2; Hui, Xiaolong1; Wang, Shuo1,3
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| 刊名 | FRONTIERS IN NEUROROBOTICS
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| 出版日期 | 2024-05-07 |
| 卷号 | 18页码:16 |
| 关键词 | service robot knowledge-enabled robot ontology knowledge representation task planning |
| ISSN号 | 1662-5218 |
| DOI | 10.3389/fnbot.2024.1401075 |
| 通讯作者 | Cai, Yinghao(yinghao.cai@ia.ac.cn) ; Wang, Shuo(shuo.wang@ia.ac.cn) |
| 英文摘要 | Introduction In recent years, the perceptual capabilities of robots have been significantly enhanced. However, the task execution of the robots still lacks adaptive capabilities in unstructured and dynamic environments.Methods In this paper, we propose an ontology based autonomous robot task processing framework (ARTProF), to improve the robot's adaptability within unstructured and dynamic environments. ARTProF unifies ontological knowledge representation, reasoning, and autonomous task planning and execution into a single framework. The interface between the knowledge base and neural network-based object detection is first introduced in ARTProF to improve the robot's perception capabilities. A knowledge-driven manipulation operator based on Robot Operating System (ROS) is then designed to facilitate the interaction between the knowledge base and the robot's primitive actions. Additionally, an operation similarity model is proposed to endow the robot with the ability to generalize to novel objects. Finally, a dynamic task planning algorithm, leveraging ontological knowledge, equips the robot with adaptability to execute tasks in unstructured and dynamic environments.Results Experimental results on real-world scenarios and simulations demonstrate the effectiveness and efficiency of the proposed ARTProF framework.Discussion In future work, we will focus on refining the ARTProF framework by integrating neurosymbolic inference. |
| WOS关键词 | KNOWLEDGE MANAGEMENT ; SERVICE ; KNOWROB |
| 资助项目 | National Natural Science Foundation of China[U23B2038] ; National Natural Science Foundation of China[62273342] |
| WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:001227545200001 |
| 出版者 | FRONTIERS MEDIA SA |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/58421]  |
| 专题 | 智能机器人系统研究 |
| 通讯作者 | Cai, Yinghao; Wang, Shuo |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China |
| 推荐引用方式 GB/T 7714 | Ge, Yueguang,Zhang, Shaolin,Cai, Yinghao,et al. Ontology based autonomous robot task processing framework[J]. FRONTIERS IN NEUROROBOTICS,2024,18:16. |
| APA | Ge, Yueguang.,Zhang, Shaolin.,Cai, Yinghao.,Lu, Tao.,Wang, Haitao.,...&Wang, Shuo.(2024).Ontology based autonomous robot task processing framework.FRONTIERS IN NEUROROBOTICS,18,16. |
| MLA | Ge, Yueguang,et al."Ontology based autonomous robot task processing framework".FRONTIERS IN NEUROROBOTICS 18(2024):16. |
入库方式： OAI收割
来源：自动化研究所
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