Details of Research Outputs

TitleIntention Understanding in Human-Robot Interaction Based on Visual-NLP Semantics
Author (Name in English or Pinyin)
Li, Zhihao1; Mu, Yishan2; Sun, Zhenglong3; Song, Sifan4; Su, Jionglong5; Zhang, Jiaming1,6
Date Issued2021-02-02
Source PublicationFrontiers in Neurorobotics
Indexed BySCIE
Education discipline科技类
Published range国外学术期刊
Volume Issue Pages卷: 14
[1] Alonso-Martín F., Castro-González A., de Gorostiza Luengo F. J. F., Salichs M. Á. (2015). Augmented robotics dialog system for enhancing human-robot interaction. Sensors 15, 15799–15829. 10.3390/s15071579926151202
[2] Dzifcak J., Scheutz M., Baral C., Schermerhorn P., (2009). What to do and how to do it: translating natural language directives into temporal and dynamic logic representation for goal management and action execution, in 2009 IEEE International Conference on Robotics and Automation (Kobe: IEEE), 4163–4168. 10.1109/ROBOT.2009.5152776
[3] Eppe M., Trott S., Feldman J., (2016). Exploiting deep semantics and compositionality of natural language for human-robot-interaction, in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Daejeon: IEEE), 731–738. 10.1109/IROS.2016.7759133
[4] Fang B., Sun F., Liu H., Liu C., (2018). 3d human gesture capturing and recognition by the immu-based data glove. Neurocomputing 277, 198–207. 10.1016/j.neucom.2017.02.101
[5] Fang B., Wei X., Sun F., Huang H., Yu Y., Liu H., (2019). Skill learning for human-robot interaction using wearable device. Tsinghua Sci. Technol. 24, 654–662. 10.26599/TST.2018.9010096
[6] Girshick R., (2015). Fast r-CNN, in Proceedings of the IEEE International Conference on Computer Vision, (Santiago) 1440–1448. 10.1109/ICCV.2015.16927295650
[7] Hatori J., Kikuchi Y., Kobayashi S., Takahashi K., Tsuboi Y., Unno Y., et al. (2018). Interactively picking real-world objects with unconstrained spoken language instructions, in 2018 IEEE International Conference on Robotics and Automation (ICRA) (Brisbane, QLD: IEEE), 3774–3781. 10.1109/ICRA.2018.8460699
[8] He K., Gkioxari G., Dollár P., Girshick R., (2017). Mask r-CNN, in Proceedings of the IEEE International Conference on Computer Vision, (Venice) 2961–2969. 10.1109/ICCV.2017.32229994331
[9] Hou J., Wu X., Zhang X., Qi Y., Jia Y., Luo J., (2020). Joint commonsense and relation reasoning for image and video captioning, in AAAI, 10973–10980. 10.1609/aaai.v34i07.6731
[10] Kalashnikov D., Irpan A., Pastor P., Ibarz J., Herzog A., Jang E., et al. (2018). Scalable deep reinforcement learning for vision-based robotic manipulation, in Conference on Robot Learning, (Zürich), 651–673.
[11] Kollar T., Tellex S., Roy D., Roy N., (2010). Toward understanding natural language directions, in 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI) (IEEE), 259–266. 10.1109/HRI.2010.5453186
[12] Lin T.-Y., Maire M., Belongie S., Hays J., Perona P., Ramanan D., et al. (2014). Microsoft COCO: common objects in context, in European Conference on Computer Vision (Amsterdam: Springer), 740–755. 10.1007/978-3-319-10602-1_48
[13] Magassouba A., Sugiura K., Quoc A. T., Kawai H., (2019). Understanding natural language instructions for fetching daily objects using gan-based multimodal target-source classification. IEEE Robot. Automat. Lett. 4, 3884–3891. 10.1109/LRA.2019.2926223
[14] Mahler J., Matl M., Satish V., Danielczuk M., DeRose B., McKinley S., et al. (2019). Learning ambidextrous robot grasping policies. Sci. Robot. 4. 10.1126/scirobotics.aau498433137754
[15] Mahler J., Pokorny F. T., Hou B., Roderick M., Laskey M., Aubry M., et al. (2016). DEX-Net 1.0: a cloud-based network of 3d objects for robust grasp planning using a multi-armed bandit model with correlated rewards, in 2016 IEEE International Conference on Robotics and Automation (ICRA) (Stockholm: IEEE), 1957–1964. 10.1109/ICRA.2016.7487342
[16] Matuszek C., Bo L., Zettlemoyer L., Fox D., (2014). Learning from unscripted deictic gesture and language for human-robot interactions. AAAI, 2556–63. 10.13016/M2RN30B52
[17] Matuszek C., Herbst E., Zettlemoyer L., Fox D., (2013). Learning to parse natural language commands to a robot control system, in Experimental Robotics (Springer), 403–415. 10.1007/978-3-319-00065-7_28
[18] Mooney R. J., (2008). Learning to connect language and perception, in AAAI, (Chicago) 1598–1601.
[19] Paul R., Barbu A., Felshin S., Katz B., Roy N., (2018). Temporal grounding graphs for language understanding with accrued visual-linguistic context. arXiv[Preprint].arXiv: 1811.06966. 10.24963/ijcai.2017/629
[20] Quillen D., Jang E., Nachum O., Finn C., Ibarz J., Levine S., (2018). Deep reinforcement learning for vision-based robotic grasping: a simulated comparative evaluation of off-policy methods, in 2018 IEEE International Conference on Robotics and Automation (ICRA) (Brisbane, QLD: IEEE), 6284–6291. 10.1109/ICRA.2018.8461039
[21] Reddy D., Raj D., (1976). Speech recognition by machine: a review. Proc. IEEE 64, 501–531. 10.1109/PROC.1976.10158
[22] Ren S., He K., Girshick R., Sun J., (2015). Faster r-cnn: towards real-time object detection with region proposal networks. IEEE transactions on pattern analysis and machine intelligence, 39, 1137–1149.27295650
[23] Richards L. E., Matuszek C., (2019). Learning to understand non-categorical physical language for human robot interactions, in From the RSS Workshop on AI and its Alternatives in Assistive and Collaborative Robotics, (Messe Freiburg).
[24] Shridhar M., Mittal D., Hsu D., (2020). INGRESS: interactive visual grounding of referring expressions. Int. J. Robot. Res. 39, 217–232. 10.1177/0278364919897133
[25] Trask A., Michalak P., Liu J., (2015). sense2vec-a fast and accurate method for word sense disambiguation in neural word embeddings. arXiv[Preprint].arXiv: 1511.06388.
[26] Uzkent B., Yeh C., Ermon S., (2020). Efficient object detection in large images using deep reinforcement learning, in The IEEE Winter Conference on Applications of Computer Vision, (Snowmass Village, CO) 1824–1833. 10.1109/WACV45572.2020.9093447
[27] Xie E., Sun P., Song X., Wang W., Liu X., Liang D., et al. (2020). Polarmask: single shot instance segmentation with polar representation, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, (Seattle, WA) 12193–12202. 10.1109/CVPR42600.2020.01221
Citation statistics
Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionSchool of Science and Engineering
Institute of Robotics and Intelligent Manufacturing
Corresponding AuthorZhang, Jiaming
1.Chinese Univ Hong Kong , Inst Robot & Intelligent Mfg, Shenzhen, Peoples R China
2.Southwestern Univ Finance & Econ, Sch Stat, Chengdu, Peoples R China
3.Chinese Univ Hong Kong , Sch Sci & Engn, Shenzhen, Peoples R China
4.Xian Jiaotong Liverpool Univ, Dept Math Sci, Suzhou, Peoples R China
5.Xian Jiaotong Liverpool Univ, XJTLU Entrepreneur Coll Taicang, Sch AI & Adv Comp, Suzhou, Peoples R China
6.Shenzhen Inst Artificial Intelligence & Robot Soc, Res Ctr Special Robots, Shenzhen, Peoples R China
Recommended Citation
GB/T 7714
Li, Zhihao,Mu, Yishan,Sun, Zhenglonget al. Intention Understanding in Human-Robot Interaction Based on Visual-NLP Semantics[J]. Frontiers in Neurorobotics,2021.
APA Li, Zhihao, Mu, Yishan, Sun, Zhenglong, Song, Sifan, Su, Jionglong, & Zhang, Jiaming. (2021). Intention Understanding in Human-Robot Interaction Based on Visual-NLP Semantics. Frontiers in Neurorobotics.
MLA Li, Zhihao,et al."Intention Understanding in Human-Robot Interaction Based on Visual-NLP Semantics".Frontiers in Neurorobotics (2021).
Files in This Item:
File Name/Size DocType File Type Version Access License
Intention Understand(1731KB)Journal article--Published draftRestricted AccessCC BY-NC-SA
Related Services
Usage statistics
Google Scholar
Similar articles in Google Scholar
[Li, Zhihao]'s Articles
[Mu, Yishan]'s Articles
[Sun, Zhenglong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Li, Zhihao]'s Articles
[Mu, Yishan]'s Articles
[Sun, Zhenglong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Li, Zhihao]'s Articles
[Mu, Yishan]'s Articles
[Sun, Zhenglong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.