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Monte Carlo Localization on a graph
Pilát, Ondřej ; Obdržálek, David (advisor) ; Iša, Jiří (referee)
This bachelor thesis concerns the Monte Carlo localization on a graph. Topics researched and solved were: movement of particles on the graph, generating particles on the edge of the graph according to the last measurements, correction from localization errors, evaluation of particles based on a different types of sensors and creation of the graph from a freely available map. The utilization of the graph as a map of environment and appropriately designed movement of particles on the graph make global localization of an autonomous robot in the environment easier. The implementation was tested on a real set of data from several autonomous robots. As a result, it was observed that movement of particles on edges of the graph well represents the movement of the robot on real paths and ensures high resistancy against senzor errors.
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Autonomous Robot Control System
Pilát, Ondřej ; Obdržálek, David (advisor) ; Bureš, Tomáš (referee)
This master thesis describes the design and implementation of control sys- tem for autonomous robot which is able to run through user defined points in unknown environment without colliding with obstacles. The work contains analysis of the available hardware and software solutions, modular design with control system implementation divided into separate subsystems (control, lo- calization, route planning, driving the robot using Hermit curves and low-level hardware control). The work also contains explanation of rework of the school robotic platform. The implementation was tested on a created robotic platform. Driving the robot along the Hermit curve allows smooth and in some cases quicker passage through defined points, than passage consisting of rotations on the spot and direct movements. 1
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Monte Carlo Localization on a graph
Pilát, Ondřej ; Obdržálek, David (advisor) ; Iša, Jiří (referee)
This bachelor thesis concerns the Monte Carlo localization on a graph. Topics researched and solved were: movement of particles on the graph, generating particles on the edge of the graph according to the last measurements, correction from localization errors, evaluation of particles based on a different types of sensors and creation of the graph from a freely available map. The utilization of the graph as a map of environment and appropriately designed movement of particles on the graph make global localization of an autonomous robot in the environment easier. The implementation was tested on a real set of data from several autonomous robots. As a result, it was observed that movement of particles on edges of the graph well represents the movement of the robot on real paths and ensures high resistancy against senzor errors.
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