The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Adapting human motion for the control of a humanoid robot
Abstract
Using the pre-recorded human motion and trajectory tracking, we can control the motion of a humanoid robot for free-space, upper body gestures. However, the number of degrees of freedom, range of joint motion, and achievable joint velocities of today's humanoid robots are far more limited than those of the average human subject. In this paper, we explore a set of techniques for limiting human motion of upper body gestures to that achievable by a Sarcos humanoid robot located at ATR. We assess the quality of the results by comparing the motion of the human actor to that of the robot, both visually and quantitatively.
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Citations
Cites
A hierarchical neural-network model for control and learning of voluntary movement
Kawato, M., Furukawa, K., & Suzuki, R. (1987) · Biological Cybernetics · doi:10.1007/bf00364149 · Cited by 1,573
Retargetting motion to new characters
Gleicher, M. (1998) · Proceedings of the 25th annual conference on Computer graphics and interactive techniques - SIGGRAPH '98 · doi:10.1145/280814.280820 · Cited by 854
Feedback-Error-Learning Neural Network for Supervised Motor Learning
Kawato, M. (1990) · Advanced Neural Computers · doi:10.1016/b978-0-444-88400-8.50047-9 · Cited by 348
Motion editing with spacetime constraints
Gleicher, M. (1997) · Proceedings of the 1997 symposium on Interactive 3D graphics - SI3D '97 · doi:10.1145/253284.253321 · Cited by 293
Computer puppetry: An importance-based approach
Shin, H. J., Lee, J., Shin, S. Y., & Gleicher, M. (2001) · ACM Transactions on Graphics · doi:10.1145/502122.502123 · Cited by 273
The impact of eye gaze on communication using humanoid avatars
Garau, M., Slater, M., Bee, S., & Sasse, M. A. (2001) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/365024.365121 · Cited by 271
Scalable Techniques from Nonparametric Statistics for Real Time Robot Learning
Schaal, S., Atkeson, C. G., & Vijayakumar, S. (2002) · Applied Intelligence · doi:10.1023/a:1015727715131 · Cited by 236
Self-citationMaking feasible walking motion of humanoid robots from human motion capture data
DasGupta, A., & Nakamura, Y. (2003) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.1999.772454 · Cited by 232
Tracking and Modifying Upper-body Human Motion Data with Dynamic Simulation
Zordan, V. B., & Hodgins, J. K. (1999) · Eurographics · doi:10.1007/978-3-7091-6423-5_2 · Cited by 78
Self-citationRiley, M., & Atkeson, C. G. (2000) · Cited by 59
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Cited by
Learning Agile Robotic Locomotion Skills by Imitating Animals
Bin Peng, X., Coumans, E., Zhang, T., Lee, T.-W., Tan, J., & Levine, S. (2020) · Robotics: Science and Systems XVI · doi:10.15607/rss.2020.xvi.064 · Cited by 357
Task-Specific Generalization of Discrete and Periodic Dynamic Movement Primitives
Ude, A., Gams, A., Asfour, T., & Morimoto, J. (2010) · IEEE Transactions on Robotics · doi:10.1109/tro.2010.2065430 · Cited by 355
Metadata
- Authors
- Pollard, N. S., Hodgins, J. K., Riley, M. J., & Atkeson, C. G.
- Venue
- Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292)
- Publisher
- IEEE
- Published
- 2003-06-25
- Volume
- 2
- Pages
- 1390-1397
- ISSN
- 1050-4729 (ISSN-L)
- OpenAlex
- W2109026728
- Cited by
- 320
- References
- 10
- FWCI
- 26.17
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Pollard, N. S., Hodgins, J. K., Riley, M. J., & Atkeson, C. G. (2003). Adapting human motion for the control of a humanoid robot. Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292). https://doi.org/10.1109/robot.2002.1014737
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