Using the Kalman Filter to Represent Probabilistic Models for Determining the Location of a Person in Collaborative Robot Working Area

The article is devoted to the study of the use of the Kalman filter for the development of probabilistic models for determining the location of a person in collaborative robot working area. The article discusses in detail the mathematical representation of the Kalman filter, including formulas for estimating and predicting system states based on measurements with noise. A software implementation of the Kalman filter was carried out, including the development of an algorithm for processing data from a video camera, which ensures accurate tracking of a person. As part of the research, a series of experiments was conducted to evaluate the effectiveness of the algorithm in real conditions, which confirms its ability to improve the accuracy of location determination and increase the safety of collaborative robots in dynamic environments.