Study of Intelligent Methods of Trajectory Construction for Mobile Robots in a Dynamic Environment

Abstract

Modern mobile robots are actively being introduced in industry, logistics, the service sector, and autonomous transport, which requires them to be able to effectively navigate dynamic and unpredictable environments. Building safe and optimal trajectories in real time is becoming a key challenge, as traditional planning methods do not provide sufficient flexibility and speed. Intelligent approaches based on optimization, machine learning, and adaptive control open up new opportunities for accounting for uncertainties, predicting object motion, and improving the efficiency of navigation systems . Research into such methods is relevant for the creation of robotic systems capable of safe and autonomous interaction with humans and the environment in the Industry 5.0 concept .