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Teaching » Syllabus: Computational Motor Control and Biomimetic Robotics

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Sept. 3


Sept. 8

Feedback Control,

Feedforward Control, Linear & Nonlinear Control

{1.1} , {1.2} , {1.3}

Sept. 15

Overview of Biological Motor Control
{2.1} , {2.2} , {2.3},

Sept. 22

Rigid Body Dynamics & Inverse Dynamics,

Supervised Learning for Motor Control

{3.1}, {3.2}, web-book

Sept. 29

Internal Models,

The Cerebellum for Motor Control

{4.1}, {4.2}

Oct. 6

Control in Systems with Time Delays,

Predictive Control  (Kalman Filters, Smith Predictors, Delay-Line Control)

{5.1}, {5.2}

Oct. 13

Classical Trajectory Planning,

Optimization Principles, Reinforcement Learning

{6.1}, {6.2}

Oct. 20

Control Hypothesis from Biology: 

Equilibrium Point Control, Minimum Jerk, Minimum Torque Change, Joint Interpolation

{7.1}, {7.2}, {7.3},


Oct. 27

Advanced Reinforcement Learning
{8.1}, {8.2}

Nov. 3

Multiple Models for Control
{9.1}, {9.2}, {9.3}

Nov. 10

no class

Nov. 17

Movement Imitation & Learning from Demonstration
{10.1}, {10.2}, {10.3}

Nov. 24

Pattern Generators for Motor Control
{11.1}, {11.2}, {11.3}

Dec. 1

{12.1}, {12.2}, {12.3}

Dec. 8

Sensorimotor Transformations 

Review of Course

{13.1}, {13.2},{13.3}

[0]Hildreth, E. C., & Hollerbach, J. M. (1985). The compuational approach to vision and motor control: Massachusetts Institute of Technology, AI Memo 846. Pages 43-68.
[1.1] Hale, F. J. (1988). Introduction to control systems analysis and design. Prentice Hall. Chapter 1.
[1.2] Martins De Carvalho, J. L. (1993). Dynamical systems and automatic control. Prentice Hall. Chapter 1.
[1.3] An, C. H., Atkeson, C. G., & Hollerbach, J. M. (1988). Model-based control of a robot manipulator. Cambridge, MA: MIT Press. Pages 16-20.
[2.1] Kandel, E. R., Schwartz, T. M. J., & Jessel, T. M. (1991). Principles of neural sciences. New York: Elsevier. Chapter 35.
[2.2] Kandel, E. R., Schwartz, T. M. J., & Jessel, T. M. (1991). Principles of neural sciences. New York: Elsevier. Chapter 40.
[2.3] Arbib, M. A. (1989). The metaphorical brain 2: Neural networks and beyond. New York: John Wiley. Pages 87-118.
[3.1] Craig, J. J. (1986). Introduction to robotics. Reading, MA: Addison-Wesley. Chapters 2.7, 2.8, 6.
[3.2] Jordan, M. I. (1996). Computational aspects of motor control and motor learning. In H. Heuer, & S. W. Keele (Eds.), Handbook of perception and action. New York: Academic Press.
[4.1] Arbib, M. A., Érdi, P., & Szentágothai, J. (1998). Neural organization

structure, function, and dynamics. Cambridge, Mass.
MIT Press. Chapter

[4.2] Kandel, E. R., Schwartz, T. M. J., & Jessel, T. M. (1991). Principles of neural sciences. New York: Elsevier. Chapter 41.
[5.1]  Miall, R. C., Weir, D. J., Wolpert, D. M., & Stein, J. F. (1993). Is the cerebellum a Smith predictor? Journal of Motor Behavior, 25, 203-216. 
[5.2]  Maybeck, P. S. (1990). The Kalman filter: An introduction to concepts. In I. J. Cox, & G. T. Wilfang (Eds.), Autonomous Robot Vehicles (pp. 194-204). New York: Springer.
[6.1]  Craig, J. J. (1986). Introduction to robotics. Reading, MA: Addison-Wesley. Chapter 7. 
[6.2]  Kirk, D. E. (1970). Optimal control theory. Englewood Cliffs, New Jersey: Prentice-Hall.
[7.1] Flanagan, J. R., Feldman, A. G., & Ostry, D. J. (1993). Control of trajectory modifications in target-directed reaching. Journal of Motor Behavior, 25, 140-152.
[7.2] Bizzi, E., Acornero, N., Chapple, W., & Hogan, N. (1984). Posture control and trajectory formation during arm movements. J. Neurosci., 4, 2738-2744.
[7.3] Flash, T., & Hogan, N. (1985). The coordination of arm movements: An experimentally confirmed mathematical model. Journal of Neurosience, 5, 1688-1703.
[7.4] Uno, Y., Kawato, M., & Suzuki, R. (1989). Formation and control of optimal trajectory in human multijoint arm movement ? Minimum torque-change model. Biol. Cybern., 61, 89-101.
[8.1] Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996). Reinforcement learning: A survey. Journal of Artificial Intelligence Research, 4, 237-285.
[8.2] Doya, K. (1996). Temporal difference learning in continuous time and space. In D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Advances in Neural Information Processing Systems 8 (pp. 913-920). Cambridge, MA: MIT Press.
[9.1] Gomi, H., and Kawato, M. Recognition of manipuulated objects by motor learning with modular architecture networks. Neural Networks 6:485-497, 1993.
[9.2] Shadmehr, R., and Brashers-Krug, T. Functional stages in the formation of human long-term motor memory. J Neurosci 17:409-419, 1997.
[9.3] Haruno, M., Wolpert, D. M., and Kawato, M. Multiple paired forward-inverse models for human motor learning and control, Advances in Neural Information Processing Systems 11. Cambridge, MA: MIT Press, 1999.
[10.1] Miyamoto, H., Schaal, S., Gandolfo, F., Koike, Y., Osu, R., Nakano, E., Wada, Y., and Kawato, M. A Kendama learning robot based on bi-directional theory. Neural Networks 9:1281-1302, 1996.
[10.2] Meltzoff, A. N., and Moore, M. K. Infant's understanding of people and things: From body imitation to folk psychology. In J. L. Bermúdez, A. Marcel, and N. Eilan (Eds.), The Body and the Self. Cambridge, MA: MIT Press, pp 43-69, 1995.
[10.3] Rizzolatti, G., Fadiga, L., Gallese, V., and Fogassi, L. Premotor cortex and the recognition of motor actions. Cognitive Brain Research 3:131-141, 1996.
[11.1] Bullock, D., Grossberg, S. (1989). VITE and FLETE: Neural modules for trajectory formation and postural control. In W.A. Hershberger (Ed.), Volitional Action. Elsevier Science Publishers.
[11.2] Matsuoka, K. (1987). Mechanisms of frequency and pattern control in the neural rhythm generators. Biological Cybernetics, 56, 345-353.
[11.3] | Schaal, S., Sternad, D. (1998). "Programmable pattern generators." <i>International Conference on Computational Intelligence in Neuroscience</i> (ICCIN'98), Research Triangle Park, NC, Oct.24-28.
[12.1]Duysens, J. and Van de Crommert Henry W.A.A. "Neural control of locomotion; Part 1: The central pattern generator from cats to humans.  <i>Gait and Posture</i>, Vol. 7, pp. 131-141, 1998.
[12.2] Taga, G., Yamaguchi, Y. and H. Shimizu.  "Self-organized control of bipedal locomtion by neural oscillators in unpredictable environment." <i> Biologidal Cybernetics</i>, Vol. 65,  pp.147-159, 1991.
[12.3] Raibert, M., Chepponis, M. and Brown, Benjamin JR.  "Running on four legs as though they were one."  <i>IEEE Journal of Robotics and Automation,</i>Vol. RA-2. No. 2, June 1986.
[13.1]  Crowe, A. Porrill, J. Prescott, T.  "Kinematic Coordination of Reach and Balance. " <i>Journal of Motor Behavior,</i> Vol. 30, No. 3, pp. 217-233, 1998.
[13.2]  Bullock, D., Grossberg, S., & Guenther, F. H. (1993). A self-organizing neural model of motor equivalent reaching and tool use by a multijoint arm. Journal of Cognitive Neuroscience, 5, 408-435..
[13.3]  Copies of  transparancies of a talk on visuomotor control.

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