Saccadic tracking for an electro-mechanical system

Electricity: motive power systems – Positional servo systems – Adaptive or optimizing systems including 'bang-bang' servos

Reexamination Certificate

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C318S560000, C318S569000, C318S568220, C318S568180

Reexamination Certificate

active

07977906

ABSTRACT:
Described is a fault-tolerant electro-mechanical system that is able to saccade to a target by training and using a signal processing technique. The invention enables tracking systems, such as next generational cameras, to be developed for autonomous platforms and surveillance systems where environment conditions are unpredictable. The invention includes at least one sensor configured to relay a signal containing positional information of a stimulus. At least one actuator is configured to manipulate the sensor to enable the sensor to track the stimulus. A processing device is configured to receive positional information from each sensor and each actuator. The processing device sends a positional changing signal to at least one actuator and adjusts at least one positional changing signal according to the information from each sensor and each actuator to enable the actuator to cause the sensor to track the stimulus.

REFERENCES:
patent: 4990838 (1991-02-01), Kawato et al.
patent: 5498943 (1996-03-01), Kimoto et al.
patent: 5774632 (1998-06-01), Kaske
patent: 7499894 (2009-03-01), Marom et al.
Piaget, J., “Commentary on Vygotsky,” New Ideas in Psychology, vol. 18, pp. 241-259, 2000.
Barto, A.G., “Reinforcement learning,” in M.A. Arbib (ed.) Handbook of Brain Theory and Neural Networks, pp. 804-809, MIT Press, Cambridge, MA 1995.
Srinivasa, N., and Sharma, R., “Execution of Saccades for active vision using a neuro-controller,” IEEE Control Systems, Special Issue on Intelligent Control, pp. 18-19, Apr. 1997.
Wei, G. Q., and Ma, S.D., “Implicit and explicit cameral calibration: theory and experiments,” IEEE trans. On Pattern Analysis and Machine Intelligence, vol. 16, pp. 469-480, 1994.
Srinivasa, N., and Ahuja, N., “A learning approach to fixate on 3D targets with active cameras,” Lecture Notes in Computer Science, vol. 1351, pp. 623-631, Springer-Verlag, Jan. 1998.
Sparks, D. and Mays, L.E., “Spatial Localization of saccade targets I: Compensation for stimulation induced perturbations in eye position,” Journal of Neurophysiology, vol. 49, pp. 45-63, 1983.
Barto, A..G., and Sutton, R.S., “Simulation of anticipatory responses in classical conditioning by a neuron-like adaptive element,” Behavioral Brain Research, vol. 4, pp. 221-235, 1982.
Bullock, D., et al., “A Self-Organizing neural model of motor equivalent reaching and tool use by a multijoint arm,” Journal of Cognitive Neuroscience, vol. 5, pp. 408-435, 1993.
Gaudiano, P. and Grossberg, S., “Vector Associative Maps: Unsupervised real-time error-based learning and control of movement trajectories,” Neural Networks, vol. 4, No. 2, pp. 147-183, 1991.
Srinivasa, N. and Sharma, R., “Efficient learning of VAM-based Representation of 3D targets and its active vision applications,” Neural Networks, vol. 11, No. 1, pp. 153-172, Jan. 1998.
Fiala, J.C., “A network of learning kinematics with application to human reaching midels,” IEEE International Conference on Neural Networks, Orlando, FL. , 1994.
M.W. Walker, D.E. Orin, “Efficient Dynamic Computer Simulation of Robotic mechanisms,” Journal of Dynamic Systems, Measurement and Control, vol. 104, pp. 205-211, 1982.

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