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Utilization of Robotic Operating System (ROS) for control of collaborative robot UR3
Juříček, Martin ; Matoušek, Radomil (referee) ; Parák, Roman (advisor)
The aim of the bachelor's thesis is to create a control program, its subsequent testing and verification of functionality for the collaborative robot UR3 from the company Universal Robots. The control program is written in python and integrates control options through the Robotic Operating System, where a defined point can be reached using pre-simulated trajectories of Q-learning, SARSA, Deep Q-learning, Deep SARSA, or using only the MoveIT framework. The thesis deals with a cross-section of the topics of collaborative robotics, Robotic Operating System, Gazebo simulation environment, feedback and deep feedback learning. Finally, the design and implementation of the control program with partial parts is described.
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Application for Communication between Volunteers and Seniors
Pomkla, František ; Hynek, Jiří (referee) ; Bartík, Vladimír (advisor)
The Moudrá Síť app provides a platform for seniors and volunteer assistants to communicate and help seniors solve digital technology problems. The main goal of this project is to educate seniors and to increase their digital literacy. This thesis focuses also on technologies for web application development, the use of CRM systems for database development, Vercel web hosting, and web accessibility. Next, the basic principles and technologies for creating chatbots are presented. The result of the thesis is a functional web application already tested by seniors as well as a comparison of two chatbot solutions based on the GPT model and the Dialogflow platform using its knowledge base.
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Utilization of Robotic Operating System (ROS) for control of collaborative robot UR3
Juříček, Martin ; Matoušek, Radomil (referee) ; Parák, Roman (advisor)
The aim of the bachelor's thesis is to create a control program, its subsequent testing and verification of functionality for the collaborative robot UR3 from the company Universal Robots. The control program is written in python and integrates control options through the Robotic Operating System, where a defined point can be reached using pre-simulated trajectories of Q-learning, SARSA, Deep Q-learning, Deep SARSA, or using only the MoveIT framework. The thesis deals with a cross-section of the topics of collaborative robotics, Robotic Operating System, Gazebo simulation environment, feedback and deep feedback learning. Finally, the design and implementation of the control program with partial parts is described.
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