计算机科学 ›› 2018, Vol. 45 ›› Issue (11A): 43-47.
龙慧, 朱定局, 田娟
LONG Hui, ZHU Ding-ju, TIAN Juan
摘要: 机器人发展的趋势是人工智能化,深度学习是智能机器人的前沿技术,也是机器学习领域的新课题。深度学习技术被广泛运用于农业、工业、军事、航空等领域,与机器人的有机结合能设计出具有高工作效率、高实时性、高精确度的智能机器人。为了增强智能机器人在各方面的能力,使其更智能化,介绍了深度学习与机器人有关的研究项目与深度学习在机器人中的各种应用,包括室内和室外的场景识别、机器人的工业服务和家庭服务以及多机器人协作等。最后,对深度学习在智能机器人中应用的未来发展、可能面临的机遇和挑战等进行了讨论。
中图分类号:
[1]王薪宇.基于深度学习和云机器人的工业机器人未来发展方向的研究[J].科技创新导报,2016,13(10):7-9. [2]YANG M,ZHU D,MUSTAFA R,et al.Learning domain-specific sentiment lexicon with supervised sentiment-aware lda[C]∥Proceedings of the Twenty-first European Conference on Artificial Intelligence.IOS Press,2014:927-932. [3]YANG M,ZHU D,TANG Y,et al.Authorship Attribution with Topic Drift Model [C]∥AAAI.2017:5015-5016. [4]MUSTAFA R,MIN Y,ZHU D.Obscenity detection using Haar-like features and gentle adaboost classifier[J].The Scientific World Journal,2014,2014:753860. [5] 黄子良.深度学习应用前景分析[J].通信与信息技术,2017(3):54-56. [6] KRIZHEVSKYK A,SUTSKEVER I,HINTON G E.Imagenet classification with deep convolutional neuralnetworks[C]∥International Conference on Neural Information Processing Systems.USA:Curran Associates Press,2012:1097-1105. [7]闫友彪,陈元琰.机器学习的主要策略综述[J].计算机应用研究,2004,21(7):4-10,13. [8]ZHU D.Feedback Big Data-Based Lie Robot[J].International Journal of Pattern Recognition and Artificial Intelligence,2018,32(2):1859002. [9]HUANG J,ZHU D,TANG Y.Health diagnosis robot based on healthcare big data and fuzzy matching[J].Journal of Intelligent &Fuzzy Systems,2017,33(5):2961-2970. [10]ZHU D,LIAN Z.Parking robot based on fuzzy reasoning and parking big data[J].Journal of Intelligent & Fuzzy Systems,2017,33(5):3087-3094. [11]ZHU D.Cloud robot system and method of integrating the same:U.S.Patent 9,031,692[P].2015-5-12. [12]ZHU D.Extendibility,Scalability and Fault-Tolerance Methods for Cloud Robots Especially for Cloud Nanorobots[J].Journal of Computational and Theoretical Nanoscience,2015,12(12):6208-6219. [13]HINTON G E,SALAKHUTDINOV R R.Reducing the dimensionality of data with neural networks[J].Science,2006,313(5786):504-507. [14]MARKOFF J.How many computers to identify a cat?[N].The New York Times,2012:6-25. [15]LECUN Y,BOSER B,DENKER J S,et al.Backpropagation applied to handwritten zip code recognition[J].Neural Computation,1989,1(4):541-551. [16] SAINATH T N,KINGSBURY B,SINDHWANI V,et al.Low-rank matrix factorization for deep neural network training with highdimensional output targets[C]∥2013 IEEE International Conference on Acoustics Speech and Singnal Processing Vancouver.Canada:IEEE Press,2013:6655-6659. [17]DONG T Y.A Simple Analysis of AlphaGo[J].Acta Automatica Sinica,2016,42(5):671-675. [18] BENGIO Y,LECUN Y.Scaling Learning Algorithms towards AI[C]∥Large-Scale Kernel Machines.2007:1-34. [19] 喻祥尤.基于深度学习的机器人场景识别研究[D].沈阳:沈阳工业大学,2017. [20]高晶钰.基于深度学习的场景识别方法研究[D].北京:北京工业大学,2015. [21]HINTON G.aPractical Guide to Training Restricted Boltzmann Manchines[J].Momentum,2012,9(1):224-238. [22]董政胤.基于分散模块化技术的机器人同时场景识别与重建[D].北京:北京工业大学,2016. [23]钱夔,宋爱国,章华涛,等.基于自主发育神经网络的机器人室内场景识别[J].机器人,2013,35(6):703-708. [24]仲训杲,徐敏,仲训昱,等.基于多模特征深度学习的机器人抓取判别方法[J].自动化学报,2016,42(7):1022-1029. [25] NGIAM J,KHOSLA A,KIM M,et al.Multimodal deep learning[C]∥Proceedings of the 28th International Conference on Machine Learning.Bellevue,USA,2011:689-696. [26] JIANG Y,MOSESON,SAXENA A.Efficient grasping from RGBD images:learning using a new rectangle representation[C]∥Proceedings of the 2011 IEEE International Conference on Robotics and Automation.Shanghai,China:IEEE,2011:3304-3311. [27]于华琛.基于深度学习的挖掘机器人图像识别及铲斗目标跟踪研究[D].南京:南京工业大学,2016. [28] FUKUSHIMA K,MIYAKE S.Neocognitron:Self-organizing network capable of position-invariant recognition of patterns[C]∥5th International Conference on Pattern Recognition.Piscata-way,USA:IEEE,1980:459-461. [29] KAVUKCUOGLU K,SERMANET P,BOUREAU Y L,et al.Learning convolutional feature hierarchies for visual recognition[C]∥24th Annual Conference on Neural Information Proces-sing Systems.USA:Curran Associates Inc,2010. [30] JADERBERG M,SIMONYAN K,VEDALDI A,et al.Reading text in the wild with convolutional neural networks[J].International Journal of Computer Vision,2016,116(1):1-20. [31]王田苗,雷静桃,魏洪兴,等.机器人系列标准介绍——服务机器人模块化设计总则及国际标准研究进展[J].机器人技术与应用,2014,4(7):1004-6437. [32] 李瀚清,房宁,赵群飞,等.利用深度去噪自编码器深度学习的指令意图理解方法[J].上海交通大学学报,2016,50(7):1102-1107. [33] VINCENT P,LAR0CHELLE H,LAJOIE I,et al.Stacked denoising autoencoders:Learning useful representations in a deep network with a local denoising criterion[J].The Journal of Machine Learning Research,2010,11(12):3371-3408. [34] SALTON G,WONG A,YANG C S.A vector space model for automatic indexing[J].Communications of the ACM,1975,18(11):613-620. [35] 梁栋.基于深度学习的目标识别研究及其多机器人编队应用[D].哈尔滨:哈尔滨工业大学,2015. [36] LONG M,GAGE A,MURPHY R,et al.Application of the Distribued Field Robot Architecture to a Simulated Deming Task[C]∥Proceedings of the International Conference on Robotics and Automation.IEEE,2005:3204-3211. [37] KOWDIKI K H,BARAI R K,BHATTACHARYA S.Leader-follower Formation Control Using Artificial Potential Functions:a Kinematic Approach[C]∥Proceedings of the International Conference on Advances in Engineering,Science and Ma-nagement.IEEE,2012:500-505. [38]DU Z,HE L,CHEN Y,et al.Robot Cloud:Bridging the power of robotics and cloud computing[J].Future Generation Compu-ter Systems,2016,21(4):301-312. [39]张小俊,刘欢欢,赵少魁,等.机器人智能化研究的关键技术与发展展望[J].机械设计,2016(8):1-7. [40]王光君.基于云计算的自主心智发育机器人研究[D].济南:山东大学,2015. [41]JI B,LI S,WANG G,et al.Could cloud technology be useful in autonomous mental developmental robotics?A case study[J].International Journal of Robotics and Automation,2016,31(3):206-444. [42]张恒,刘艳丽,刘大勇.云机器人的研究进展[J].计算机应用研究,2014,31(9):2567-2575. |
[1] | 饶志双, 贾真, 张凡, 李天瑞. 基于Key-Value关联记忆网络的知识图谱问答方法 Key-Value Relational Memory Networks for Question Answering over Knowledge Graph 计算机科学, 2022, 49(9): 202-207. https://doi.org/10.11896/jsjkx.220300277 |
[2] | 冷典典, 杜鹏, 陈建廷, 向阳. 面向自动化集装箱码头的AGV行驶时间估计 Automated Container Terminal Oriented Travel Time Estimation of AGV 计算机科学, 2022, 49(9): 208-214. https://doi.org/10.11896/jsjkx.210700028 |
[3] | 宁晗阳, 马苗, 杨波, 刘士昌. 密码学智能化研究进展与分析 Research Progress and Analysis on Intelligent Cryptology 计算机科学, 2022, 49(9): 288-296. https://doi.org/10.11896/jsjkx.220300053 |
[4] | 汤凌韬, 王迪, 张鲁飞, 刘盛云. 基于安全多方计算和差分隐私的联邦学习方案 Federated Learning Scheme Based on Secure Multi-party Computation and Differential Privacy 计算机科学, 2022, 49(9): 297-305. https://doi.org/10.11896/jsjkx.210800108 |
[5] | 徐涌鑫, 赵俊峰, 王亚沙, 谢冰, 杨恺. 时序知识图谱表示学习 Temporal Knowledge Graph Representation Learning 计算机科学, 2022, 49(9): 162-171. https://doi.org/10.11896/jsjkx.220500204 |
[6] | 李瑶, 李涛, 李埼钒, 梁家瑞, Ibegbu Nnamdi JULIAN, 陈俊杰, 郭浩. 基于多尺度的稀疏脑功能超网络构建及多特征融合分类研究 Construction and Multi-feature Fusion Classification Research Based on Multi-scale Sparse Brain Functional Hyper-network 计算机科学, 2022, 49(8): 257-266. https://doi.org/10.11896/jsjkx.210600094 |
[7] | 王剑, 彭雨琦, 赵宇斐, 杨健. 基于深度学习的社交网络舆情信息抽取方法综述 Survey of Social Network Public Opinion Information Extraction Based on Deep Learning 计算机科学, 2022, 49(8): 279-293. https://doi.org/10.11896/jsjkx.220300099 |
[8] | 郝志荣, 陈龙, 黄嘉成. 面向文本分类的类别区分式通用对抗攻击方法 Class Discriminative Universal Adversarial Attack for Text Classification 计算机科学, 2022, 49(8): 323-329. https://doi.org/10.11896/jsjkx.220200077 |
[9] | 姜梦函, 李邵梅, 郑洪浩, 张建朋. 基于改进位置编码的谣言检测模型 Rumor Detection Model Based on Improved Position Embedding 计算机科学, 2022, 49(8): 330-335. https://doi.org/10.11896/jsjkx.210600046 |
[10] | 张光华, 高天娇, 陈振国, 于乃文. 基于N-Gram静态分析技术的恶意软件分类研究 Study on Malware Classification Based on N-Gram Static Analysis Technology 计算机科学, 2022, 49(8): 336-343. https://doi.org/10.11896/jsjkx.210900203 |
[11] | 何强, 尹震宇, 黄敏, 王兴伟, 王源田, 崔硕, 赵勇. 基于大数据的进化网络影响力分析研究综述 Survey of Influence Analysis of Evolutionary Network Based on Big Data 计算机科学, 2022, 49(8): 1-11. https://doi.org/10.11896/jsjkx.210700240 |
[12] | 孙奇, 吉根林, 张杰. 基于非局部注意力生成对抗网络的视频异常事件检测方法 Non-local Attention Based Generative Adversarial Network for Video Abnormal Event Detection 计算机科学, 2022, 49(8): 172-177. https://doi.org/10.11896/jsjkx.210600061 |
[13] | 胡艳羽, 赵龙, 董祥军. 一种用于癌症分类的两阶段深度特征选择提取算法 Two-stage Deep Feature Selection Extraction Algorithm for Cancer Classification 计算机科学, 2022, 49(7): 73-78. https://doi.org/10.11896/jsjkx.210500092 |
[14] | 程成, 降爱莲. 基于多路径特征提取的实时语义分割方法 Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction 计算机科学, 2022, 49(7): 120-126. https://doi.org/10.11896/jsjkx.210500157 |
[15] | 侯钰涛, 阿布都克力木·阿布力孜, 哈里旦木·阿布都克里木. 中文预训练模型研究进展 Advances in Chinese Pre-training Models 计算机科学, 2022, 49(7): 148-163. https://doi.org/10.11896/jsjkx.211200018 |
|