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Control of the belt robot
Vávra, Jakub ; Kopečný, Lukáš (referee) ; Macho, Tomáš (advisor)
This semester thesis deals with the management of autonomous robot crawler. The robot will be able to avoid obstacles and check if there are on the mat. Will assess whether or not the barrier is to the left or right of it, and hence it avoids.
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Navigace mobilních robotů v neznámém prostředí s využitím měření vzdáleností
Jež, Ondřej ; Žalud, Luděk (advisor)
The ability of a robot to navigate itself in the environment is a crucial step towards its autonomy. Navigation as a subtask of the development of autonomous robots is the subject of this thesis, focusing on the development of a method for simultaneous localization an mapping (SLAM) of mobile robots in six degrees of freedom (DOF). As a part of this research, a platform for 3D range data acquisition based on a continuously inclined laser rangefinder was developed. This platform is presented, evaluating the measurements and also presenting the robotic equipment on which the platform can be fitted. The localization and mapping task is equal to the registration of multiple 3D images into a common frame of reference. For this purpose, a method based on the Iterative Closest Point (ICP) algorithm was developed. First, the originally implemented SLAM method is presented, focusing on the time-wise performance and the registration quality issues introduced by the implemented algorithms. In order to accelerate and improve the quality of the time-demanding 6DOF image registration, an extended method was developed. The major extension is the introduction of a factorized registration, extracting 2D representations of vertical objects called leveled maps from the 3D point sets, ensuring these representations are 3DOF invariant. The extracted representations are registered in 3DOF using ICP algorithm, allowing pre-alignment of the 3D data for the subsequent robust 6DOF ICP based registration. The extended method is presented, showing all important modifications to the original method. The developed registration method was evaluated using real 3D data acquired in different indoor environments, examining the benefits of the factorization and other extensions as well as the performance of the original ICP based method. The factorization gives promising results compared to a single phase 6DOF registration in vertically structured environments. Also, the disadvantages of the method are discussed, proposing possible solutions. Finally, the future prospects of the research are presented.
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Mapping a confined area using a mobile robot
Dolák, Šimon ; Nevoral, Tomáš (referee) ; Holoubek, Tomáš (advisor)
This thesis focuses on the setup of the TurtleBot3 Burger robot in the ROS (Robot Operating System) environment and the development of assigned laboratory tasks. One of the tasks involves navigating the robot in a closed unknown environment, utilizing sensors and algorithms for mapping and localization. The second task involves reading QR codes. Both programs are developed in the simulation environment Gazebo and applicable to a real robot. The thesis also includes a brief review of mobile robots and the Robot Operating System.
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Trajectory planning for fast moving cars
Rozsíval, Šimon ; Barták, Roman (advisor) ; Obdržálek, David (referee)
The goal of this thesis is to create an artificial agent for an autonomous racing vehicle. This project is inspired by the F1/10 racing competition. The agent uses a planning algorithm to find a time-optimal trajectory. To achieve real-time performance, the agent analyzes the map of the track and it plans only for the next two corners immediately ahead of the vehicle. The agent re-plans several times per second as it drives along the circuit to account for imprecise trajectory following. We successfully tested the agent in the Gazebo simulator with good results. We also tested the algorithm on a custom car-like robot equipped with an on-board computer and sensors, but with limited success. 1
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Control of the belt robot
Vávra, Jakub ; Kopečný, Lukáš (referee) ; Macho, Tomáš (advisor)
This semester thesis deals with the management of autonomous robot crawler. The robot will be able to avoid obstacles and check if there are on the mat. Will assess whether or not the barrier is to the left or right of it, and hence it avoids.
|
|
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Control of the belt robot
Vávra, Jakub ; Kopečný, Lukáš (referee) ; Macho, Tomáš (advisor)
This semester thesis deals with the management of autonomous robot crawler. The robot will be able to avoid obstacles and check if there are on the mat. Will assess whether or not the barrier is to the left or right of it, and hence it avoids.
|
|
|
Navigace mobilních robotů v neznámém prostředí s využitím měření vzdáleností
Jež, Ondřej ; Žalud, Luděk (advisor)
The ability of a robot to navigate itself in the environment is a crucial step towards its autonomy. Navigation as a subtask of the development of autonomous robots is the subject of this thesis, focusing on the development of a method for simultaneous localization an mapping (SLAM) of mobile robots in six degrees of freedom (DOF). As a part of this research, a platform for 3D range data acquisition based on a continuously inclined laser rangefinder was developed. This platform is presented, evaluating the measurements and also presenting the robotic equipment on which the platform can be fitted. The localization and mapping task is equal to the registration of multiple 3D images into a common frame of reference. For this purpose, a method based on the Iterative Closest Point (ICP) algorithm was developed. First, the originally implemented SLAM method is presented, focusing on the time-wise performance and the registration quality issues introduced by the implemented algorithms. In order to accelerate and improve the quality of the time-demanding 6DOF image registration, an extended method was developed. The major extension is the introduction of a factorized registration, extracting 2D representations of vertical objects called leveled maps from the 3D point sets, ensuring these representations are 3DOF invariant. The extracted representations are registered in 3DOF using ICP algorithm, allowing pre-alignment of the 3D data for the subsequent robust 6DOF ICP based registration. The extended method is presented, showing all important modifications to the original method. The developed registration method was evaluated using real 3D data acquired in different indoor environments, examining the benefits of the factorization and other extensions as well as the performance of the original ICP based method. The factorization gives promising results compared to a single phase 6DOF registration in vertically structured environments. Also, the disadvantages of the method are discussed, proposing possible solutions. Finally, the future prospects of the research are presented.
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