Перегляд за автором "Murad Anver oglu Omarov"

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  • Зображення мініатюри
    Публікація
    Methods for Optimizing the Building of Collaborative Robot Routes in a Dynamic Environment
    («SCIENTIA», 2025) Nevliudov, I. Sh.; Murad Anver oglu Omarov; Yevsieiev, V.; Elgun Jabrayilzade
    Modern collaborative robots (cobots), which work alongside humans in a shared workspace, must plan trajectories that simultaneously meet the requirements of safety, smooth motion, timely responsiveness to dynamic obstacles (people, other robots, moving objects), energy efficiency, and task accuracy. The dynamic environment imposes additional constraints on the planner: incomplete information about future obstacle trajectories, uncertainty in sensor measurements, rigid kinematic/dynamic constraints of the robot, and the need for fast real-time response. Because of this, trajectory optimization in a collaborative context usually requires a combination of: predictive models of human/obstacle behavior, rapid local corrections, and global optimality criteria — which is why the comparison of methods should focus not only on “trajectory quality” but also on computational costs, safety guarantees, and integration with human behavior prediction.
  • Зображення мініатюри
    Публікація
    Study of Intelligent Methods of Trajectory Construction for Mobile Robots in a Dynamic Environment
    (LLC Boston Data Science Group, 2025) Nevliudov, I. Sh.; Murad Anver oglu Omarov; Yevsieiev, V.; Elgun Jabrayilzade
    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 .