Sirvi Autor "Hurova, Iryna" järgi

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Kitting station of the learning factory
(Tartu Ülikool, 2023) Hurova, Iryna; Kruusamäe, Karl, juhendaja; Vunder, Veiko, juhendaja
Learning factories has become a new educational approach that allows students to get hands-on experience working in a simplified factory environment. The aim of this thesis is to assemble a multi-robot setup where two or more autonomous robots can communicate with each other to achieve the desired goal. Robot Operating System (ROS) is used to create software for the manipulator robot in the kitting station, which figures as one of the components of the learning factory.
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Model-based planning using GPU-accelerated Simulator as a World Model
(Tartu Ülikool, 2025) Hurova, Iryna; Singh, Arun Kumar, juhendaja; Kruusamäe, Karl, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Manipulator robots are increasingly deployed in real-world tasks that require smooth, reactive motion and robust collision avoidance, particularly in dynamic and unstructured environments. This thesis presents a model-based, collision-free, online trajectory optimization framework tailored for such scenarios. The method involves sampling hundreds of trajectories from a multivariate normal distribution, shaping them with Bernstein polynomials, and evaluating them in parallel within a MuJoCo simulation. These trajectories are then optimized using the cross-entropy method. The system achieves real-time, in-the-loop planning by integrating a model predictive control strategy. The experiment, both in simulation and in real-world tests, demonstrated successful manipulation in an environment with multiple obstacles. In addition, the framework supports flexible task objectives by adjusting the cost function, enabling goal-driven behavior under varying conditions.