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Mobile Robot Localization in Indoor Scenarios
Sýkora, Tomáš ; Brejcha, Jan (referee) ; Beran, Vítězslav (advisor)
The goal of this project was to create a software for an autonomous mobile robot capable of navigation in indoor scenarios and of detection and recognition of the objects on its way. An important condition that the final software had to meet was to find the cheapest solution possible. I achieved the given goal and its conditions using an open source software framework Robotic Operating System (ROS) and its tools. The final system is a set of ROS modules communicating with each other, using a single sensor as an input data stream and a small motor which is able to send information about its velocity and rotations to the control part of the system. This mobile robot can, without any significant problems, navigate through a mapped area while trying to find trained objects. Such a robot could be easily used (after adding specific mechanical parts) to help retired or disabled people, to cooperate with industry workers or in many other fields.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Uhlíř, Václav (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors, provide sensor fusion and estimate position of robot based on this fusion. For solving I used knowledge about probabilistic robotics, robotic operating system, information fusion, filtering especially extended Kalman filter and robot localization. I created an application of extended Kalman filter as a result. Filter listen to messages from robot sensors, providing a sensor fusion and estimating position of the robot in environment. Filter can receive measurements from multiple sources. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Žák, Marek (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors and fuse them together. Afterwards use this data fusion of chosen sensors to estimate location of a robot. As a solution for these problems I have used my knowledge of Kalman filters, especially extended one. If messages from sensor measurements are well formulated, Kalman filter can perform fusion of measurements together with estimating the actual position of a robot. Filter can receive measurements from multiple sources and even from duplicities. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Žák, Marek (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors and fuse them together. Afterwards use this data fusion of chosen sensors to estimate location of a robot. As a solution for these problems I have used my knowledge of Kalman filters, especially extended one. If messages from sensor measurements are well formulated, Kalman filter can perform fusion of measurements together with estimating the actual position of a robot. Filter can receive measurements from multiple sources and even from duplicities. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
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|
|
Robot Positioning Based on Sensor Measurements
Čakloš, Ondrej ; Uhlíř, Václav (referee) ; Rozman, Jaroslav (advisor)
The goal of this thesis is to create a program, that will be receiving measurements from robot's sensors, provide sensor fusion and estimate position of robot based on this fusion. For solving I used knowledge about probabilistic robotics, robotic operating system, information fusion, filtering especially extended Kalman filter and robot localization. I created an application of extended Kalman filter as a result. Filter listen to messages from robot sensors, providing a sensor fusion and estimating position of the robot in environment. Filter can receive measurements from multiple sources. The estimated states have proven themselves reasonably accurate for successful robot localization in space.
|
|
|
Mobile Robot Localization in Indoor Scenarios
Sýkora, Tomáš ; Brejcha, Jan (referee) ; Beran, Vítězslav (advisor)
The goal of this project was to create a software for an autonomous mobile robot capable of navigation in indoor scenarios and of detection and recognition of the objects on its way. An important condition that the final software had to meet was to find the cheapest solution possible. I achieved the given goal and its conditions using an open source software framework Robotic Operating System (ROS) and its tools. The final system is a set of ROS modules communicating with each other, using a single sensor as an input data stream and a small motor which is able to send information about its velocity and rotations to the control part of the system. This mobile robot can, without any significant problems, navigate through a mapped area while trying to find trained objects. Such a robot could be easily used (after adding specific mechanical parts) to help retired or disabled people, to cooperate with industry workers or in many other fields.
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