Object Recognition Method Based on Their Signal-Geometric Signs through a Robotic Security Complex

• Published in: Mathematical models and computer simulations Vol. 15; no. 2; pp. 297 - 311
• Main Authors: Pushkarev, Y. A., Sviridov, V. V.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.04.2023; Springer Nature B.V
• Subjects: Adaptive control; Distribution functions; Energy distribution; Mathematical analysis; Mathematical Modeling and Industrial Mathematics; Mathematics; Mathematics and Statistics; Object recognition; Optoelectronics; Parameters; Robot control; Robotics; Simulation and Modeling; Task complexity; adaptive group control; feature space; probability of correct recognition; robotic complex; a posteriori probability; probability of omission; likelihood function; object
• ISSN: 2070-0482; 2070-0490
• DOI: 10.1134/S207004822302014X

This article considers a methodological approach to recognize the intrusion of objects into a protected area using an optoelectronic robotic complex, which is based on the existence of a certain characteristic space (a set of signal and geometric features) for each class and type of object. The solved problem of comparing Bayesian a posteriori probabilities of classes (types) of objects is reduced to calculating a priori probabilities and energy distribution functions of signals and geometric parameters of objects, i.e., the likelihood functions of a feature for a specific class (type) of an object. Based on the obtained parameters, the dependences of the probability of correct recognition, omission, false recognition, and confusion of objects on the coefficient of distinctness when the object’s signal energy deviates from the standard energy are analyzed. The results obtained are required to solve the problem of the adaptive group control of robotic complexes when solving operational and tactical and tasks in an uncertain dynamic environment.