Data processing: vehicles – navigation – and relative location – Vehicle control – guidance – operation – or indication – Construction or agricultural-type vehicle
Patent
1998-10-14
2000-06-13
Cuchlinski, Jr., William A.
Data processing: vehicles, navigation, and relative location
Vehicle control, guidance, operation, or indication
Construction or agricultural-type vehicle
701207, 37414, 172 45, G06F 1900
Patent
active
060760303
ABSTRACT:
In one embodiment of the present invention, a motion planning algorithm is used to control an autonomous machine. The motion planning algorithm consists of a template or script which captures the general trends of the motion, while parameters in the script are filled in with the kinematic details for a specific machine and set of movements. A learning algorithm computes the script parameters by using feedback of how the machine performed during the preceding cycle with the current parameter set, and adjusting the parameters to improve the machine's performance during succeeding work cycles. The new parameters are evaluated by the learning algorithm using a predictive function approximator to test various performance criteria such as the time required to perform a task and the accuracy with which the task was performed. The performance criteria are weighted using local regression techniques so that the prediction of the outcome of alternate motions places emphasis on the performance criteria that is considered most important. As data from repeated motions accumulates, the algorithm uses the history of the results of various motions to recompute and refine the parameters to improve performance.
REFERENCES:
patent: 5631658 (1997-05-01), Gudat
P. Rowe & A. Stentz, Parameterized Scripts for Motion Planning, Proceeding of the International Conference on Intelligent Robots & Systems, vol. 2, pp. 1119-1125, Sep. 10, 1997.
P.J.A. Lever & F. Wang, Intelligent Excavator Control System for Lunar Mining System, Journal of Aerospace Engineering, vol. 8, No. 1, 1995.
X. Shi, P. Lever & F. Wang, Experimental Robotic Excavation with Fuzzy Logic & Neural Networks, Proceedings of the International Conference on Robotics & Automation, 1996.
S. Singh, Learning to Predict Resistive Forces During Robotic Excavation, Proceedings of the International Confrence on Robotics & Automation, 1995.
B. Song & A.J. Koivo, Neural Adaptive Control of Excavators, Proceedings of the International Conference on Intelligent Robots & Systems, vol. 1, pp. 162-167, 1995.
Carnegie Mellon University
Cuchlinski Jr. William A.
Donnelly Arthur D.
LandOfFree
Learning system and method for optimizing control of autonomous does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Learning system and method for optimizing control of autonomous , we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Learning system and method for optimizing control of autonomous will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-2077881