1 |
GOODFELLOW I, BENGIO Y, COURVILLE A. Chapter 5: Machine learning basics[M]// Deep Learning. Cambridge: MIT Press, 2016: 96-161.
|
2 |
LeCUN Y, BENGIO Y, HINTON G. Deep learning[J]. Nature, 2015, 521(7553): 436-444. 10.1038/nature14539
|
3 |
RAINA A, McCOMB C, CAGAN J. Learning to design from humans: imitating human designers through deep learning[J]. Journal of Mechanical Design, 2019, 141(11): No.111102. 10.1115/1.4044256
|
4 |
HUA J, ZENG L C, LI G F, et al. Learning for a robot: deep reinforcement learning, imitation learning, transfer learning[J]. Sensors, 2021, 21(4): No.1278. 10.3390/s21041278
|
5 |
DOERING M, GLAS D F, ISHIGURO H. Modeling interaction structure for robot imitation learning of human social behavior[J]. IEEE Transactions on Human-Machine Systems, 2019, 49(3): 219-231. 10.1109/thms.2019.2895753
|
6 |
SCHERZINGER S, ROENNAU A, DILLMANN R. Contact skill imitation learning for robot-independent assembly programming[C]// Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway: IEEE, 2019: 4309-4316. 10.1109/iros40897.2019.8967523
|
7 |
FERI L E, AHN J, LUTFILLOHONOV S, et al. A three-dimensional microstructure reconstruction framework for permeable pavement analysis based on 3D-IWGAN with enhanced gradient penalty[J]. Sensors, 2021, 21(11): No.3603. 10.3390/s21113603
|
8 |
LI H Q, WANG R H. Method of real-time wellbore surface reconstruction based on spiral contour[J]. Energies, 2021, 14(2): No.291. 10.3390/en14020291
|
9 |
刘东生,陈建林,费点,等. 基于深度相机的大场景三维重建[J]. 光学精密工程, 2020, 28(1):234-243. 10.3788/ope.20202801.0234
|
|
LIU D S, CHEN J L, FEI D, et al. Three-dimensional reconstruction of large-scale scene based on depth camera[J]. Optics Precision Engineering, 2020, 28(1):234-243. 10.3788/ope.20202801.0234
|
10 |
HENRY P, KRAININ M, HERBST E, et al. RGB-D mapping: using Kinect-style depth cameras for dense 3D modeling of indoor environments[J]. The International Journal of Robotics Research, 2012, 31(5): 647-663. 10.1177/0278364911434148
|
11 |
NEWCOMBE R A, IZADI S, HILLIGES O, et al. KinectFusion: real-time dense surface mapping and tracking[C]// Proceedings of the 10th IEEE International Symposium on Mixed and Augmented Reality. Piscataway: IEEE, 2011: 127-136. 10.1109/ismar.2011.6092378
|
12 |
FURUKAWA Y, Accurate PONCE J., dense, and robust multiview stereopsis [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(8): 1362-1376. 10.1109/tpami.2009.161
|
13 |
TORKINGTON J, SMITH S G T, REES B I, et al. Skill transfer from virtual reality to a real laparoscopic task[J]. Surgical Endoscopy, 2001, 15(10): 1076-1079. 10.1007/s004640000233
|
14 |
LIU Y Y, LI Z J, LIU H P, et al. Skill transfer learning for autonomous robots and human-robot cooperation: a survey[J]. Robotics and Autonomous Systems, 2020, 128: No.103515. 10.1016/j.robot.2020.103515
|
15 |
SUN Y, GUO Q Q, ZHAO S M, et al. Context-aware augmented reality using human-computer interaction models[J/OL]. Journal of Control and Decision (2022-01-24) [2022-02-10].. 10.1080/23307706.2022.2026260
|
16 |
马子玉,何明,刘祖均,等. 无人机协同控制研究综述[J]. 计算机应用, 2021, 41(5): 1477-1483. 10.11772/j.issn.1001-9081.2020081314
|
|
MA Z Y, HE M, LIU Z J, et al. Survey of unmanned aerial vehicle cooperative control[J]. Journal of Computer Applications, 2021, 41(5): 1477-1483. 10.11772/j.issn.1001-9081.2020081314
|
17 |
BREAZEAL C, SCASSELLATI B. Robots that imitate humans[J]. Trends in Cognitive Sciences, 2002, 6(11): 481-487. 10.1016/s1364-6613(02)02016-8
|
18 |
EDSINGER A, KEMP C C. Human-robot interaction for cooperative manipulation: handing objects to one another[C]// Proceedings of the 16th IEEE International Symposium on Robot and Human Interactive Communication. Piscataway: IEEE, 2007: 1167-1172. 10.1109/roman.2007.4415256
|
19 |
ZHU Z Y, HU H S. Robot learning from demonstration in robotic assembly: a survey[J]. Robotics, 2018, 7(2): No.17. 10.3390/robotics7020017
|
20 |
RAVICHANDAR H, POLYDOROS A S, CHERNOVA S, et al. Recent advances in robot learning from demonstration[J]. Annual Review of Control, Robotics, and Autonomous Systems, 2020, 3: 297-330. 10.1146/annurev-control-100819-063206
|
21 |
HAVOUTIS I, CALINON S. Learning from demonstration for semi-autonomous teleoperation[J]. Autonomous Robots, 2019, 43(3): 713-726. 10.1007/s10514-018-9745-2
|
22 |
张继凯,赵君,张然,等. 深度学习的图像实例分割方法综述[J]. 小型微型计算机系统, 2021, 42(1): 161-71. 10.3969/j.issn.1000-1220.2021.01.028
|
|
ZHANG J K, ZHAO J, ZHANG R, et al. Survey of image instance segmentation methods based on deep learning[J]. Journal of Chinese Computer Systems, 2021, 42(1): 161-71. 10.3969/j.issn.1000-1220.2021.01.028
|
23 |
REN S Q, HE K M, GIRSHICK R. Faster R-CNN: towards real-time object detection with region proposal networks[C]// Proceedings of the 28th International Conference on Neural Information Processing Systems - Volume 1. Cambridge: MIT Press, 2015:91-99.
|
24 |
LIN T Y, DOLLÁR P, GIRSHICK R. Feature pyramid networks for object detection[C]// Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition. Piscataway: IEEE, 2017: 936-944. 10.1109/cvpr.2017.106
|
25 |
中国科学院自动化研究所. 面向执行器操作空间的RGBD视觉实时重建方法及系统: 202110642486.9[P]. 2021-08-17.
|
|
Institute of Automation of Chinese Academy of Sciences. RGBD visual real-time reconstruction method and system for actuator operation space: 202110642486.9[P]. 2021-08-17.
|