Learning Humanoid Arm Gestures
@inproceedings{Adams2005LearningHA, title={Learning Humanoid Arm Gestures}, author={B. Adams}, year={2005} }
While biological motion control systems are generally simple and robust, their robotic analogs tend to be just the opposite. While function has driven many of the control architectures to date, we feel that a biologically-inspired system for monitoring the energy consumption of virtual muscles can lead to the development of more humanoid motion and gesture.
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References
SHOWING 1-10 OF 16 REFERENCES
Inverse kinematics for humanoid robots
- Mathematics, Computer Science
- Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)
- 2000
- 140
- PDF
The human arm as a redundant manipulator: The control of path and joint angles
- Engineering, Medicine
- Biological Cybernetics
- 2004
- 85
- PDF
Fast and efficient incremental learning for high-dimensional movement systems
- Mathematics, Computer Science
- Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)
- 2000
- 40
- PDF
Meso: A virtual musculature for humanoid robots
- Meso: A virtual musculature for humanoid robots
- 2000
Inverse kinematics for humanoid
- 1999