The use of a robot-vision-tracking system to efficiently process different types of objects presented randomly on a moving conveyor belt requires the system to schedule pick and place operations of the robot to minimize robot processing times and avoid constraint violations. In this paper we present a new approach: a modified ARTMAP neural network is incorporated in the robot-vision-tracking system as an “intelligent” component to on-line schedule pick-place operations in order to obtain optimal orders for any group of objects. When the robot-vision-tracking system is working in a changing environment, the neural networks used in the optimal scheduling task must be capable of updating their weights aperiodically based on the data collected intermittently in real operations in order to create a continuously effective system. The ARTMAP network developed by Carpenter et al, (1991), which can rapidly learn mappings between binary input and binary output vectors by using a supervised learning law, has good properties to deal with this task. In special situations, however, the ARTMAP must employ a complement coding technique to preprocess incoming patterns to be presented to the network. This doubles the size of input patterns and increases learning time. The Modified ARTMAP network, proposed herein, copes with these special situations without using complement coding, and has been shown to increase the overall system speed. The basic idea is to insert a matching check mechanism that internally changes the learning order of input vector pairs in responding to an arbitrary sequence of arriving input vector pairs. Simulation results are presented for scheduling a number of different objects, demonstrating a substantial improvement in learning speed and accuracy.
Skip Nav Destination
Article navigation
March 1996
Technical Papers
A Modified ARTMAP Network, With Applications to Scheduling of a Robot-Vision-Tracking System
K. Feng,
K. Feng
School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078
Search for other works by this author on:
L. L. Hoberock
L. L. Hoberock
School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078
Search for other works by this author on:
K. Feng
School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078
L. L. Hoberock
School of Mechanical and Aerospace Engineering, Oklahoma State University, Stillwater, OK 74078
J. Dyn. Sys., Meas., Control. Mar 1996, 118(1): 1-8 (8 pages)
Published Online: March 1, 1996
Article history
Received:
May 12, 1992
Online:
December 3, 2007
Citation
Feng, K., and Hoberock, L. L. (March 1, 1996). "A Modified ARTMAP Network, With Applications to Scheduling of a Robot-Vision-Tracking System." ASME. J. Dyn. Sys., Meas., Control. March 1996; 118(1): 1–8. https://doi.org/10.1115/1.2801146
Download citation file:
Get Email Alerts
Cited By
Robust Fault Detection for Unmanned Aerial Vehicles Subject to Denial-of-Service Attacks
J. Dyn. Sys., Meas., Control
Vibration Suppression and Trajectory Tracking with Nonlinear Model Predictive Control for UAM Aircraft
J. Dyn. Sys., Meas., Control
Learning battery model parameter dynamics from data with recursive Gaussian process regression
J. Dyn. Sys., Meas., Control
An Integrated Sensor Fault Estimation and Fault-Tolerant Control Design Approach for Continuous-Time Switched Systems
J. Dyn. Sys., Meas., Control (July 2025)
Related Articles
Adaptive Neural Control of Walking Robots
Appl. Mech. Rev (January,2002)
Optimizing 3D Laser Foil Printing Parameters for AA 6061: Numerical and Experimental Analysis
J. Manuf. Sci. Eng (March,2025)
A Task-Space Tracking Control Approach for Duct Cleaning Robot Based on Fuzzy Wavelet Neural Network
J. Dyn. Sys., Meas., Control (November,2019)
Nonlinear Manipulation Control of a Compliant Object by Dual Fingers
J. Dyn. Sys., Meas., Control (September,2006)
Related Proceedings Papers
Related Chapters
Spiking Neural Networks on Self-Updating System-on-Chip for Autonomous Control
International Conference on Mechanical Engineering and Technology (ICMET-London 2011)
Modeling and Simulation of Coal Gas Concentration Prediction Based on the BP Neural Network
International Symposium on Information Engineering and Electronic Commerce, 3rd (IEEC 2011)
A Semi-Adaptive Fractional Order PID Control Strategy for a Certain Gun Control Equipment
International Conference on Instrumentation, Measurement, Circuits and Systems (ICIMCS 2011)