There is no abstract available for this article.
This work was supported by National Natural Science Foundation of China (Grant No. 51775333).
[1] Wachter M, Asfour T. Hierarchical segmentation of manipulation actions based on object relations and motion characteristics. In: Proceedings of International Conference on Advanced Robotics, 2015. 549--556. Google Scholar
[2] Lim G H. Two-step learning about normal and exceptional human behaviors incorporating patterns and knowledge. In: Proceedings of IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, 2017. 162--167. Google Scholar
[3] Ding H, Yang X, Zheng N. Tri-Co Robot: a Chinese robotic research initiative for enhanced robot interaction capabilities. Natl Sci Rev, 2018, 5: 799-801 CrossRef Google Scholar
[4] Argall B D, Chernova S, Veloso M. A survey of robot learning from demonstration. Robotics Autonomous Syst, 2009, 57: 469-483 CrossRef Google Scholar
[5] Langevin G. Inmoov. 2014. http://www.inmoov.fr/ project. Google Scholar
[6] Gong L, Gong C, Ma Z, et al. Real-time human-in-the-loop remote control for a lifesize traffic police robot with multiple augmented reality aided display terminals. In: Proceedings of the 2nd International Conference on Advanced Robotics and Mechatronics (ICARM), 2017. 420--425. Google Scholar
[7] Meng X, Pan J, Qin H. Motion capture and retargeting of fish by monocular camera. In: Proceedings of International Conference on Cyberworlds, 2017. 80--87. Google Scholar
[8] Dai H, Cai B, Song J, et al. Skeletal animation based on bvh motion data. In: Proceedings of the 2nd International Conference on Information Engineering and Computer Science, 2010. 1--4. Google Scholar
Figure 1
Natural teaching process. (a) Humanoid natural teaching system; (b) task starting point; (c) task end point; (d) frames during teaching process; and (e) error during teaching process.
Download PDF
