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Covering the Working Space of Mobile Robot
Krejsa, Jiří ; Věchet, Stanislav
Equally distributed covering of working space is essential in some mobile robot applications, such as presentation robotics or security robot patrol. This paper explores a method for such covering based on rapidly exploring random trees (RRT) algorithm. RRTs can cover the working space close to completeness while uncovered areas are quickly reduced. The algorithm can be modified to emphasize certain areas of interest by appropriately generating corresponding goals. Method performance is compared to random walk in simulation experiments.
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Multiple Indoor Robot Localization Using Infrared Beacons
Krejsa, Jiří ; Věchet, Stanislav ; Chen, K.-S.
Mobile robot localization based on active artificial landmarks is well established robust technique in indoor mobile robotics. This paper explores the extension of the method to multiple robot localization, with the key idea of using the robots themselves as the artificial landmarks, supplying other robots in the group with its estimate of position. The method uses nonlinear version of Kalman filter for determination of position estimate in 2D space, x-y coordinates and angle with respect to global coordinate system, with the estimate represented by mean values and corresponding covariances. Simulation results based on model well verified with the real system suggest that while only small reduction of number of fixed active landmarks can be achieved, the main advantage of the method is in increased robustness of localization technique with respect to obscured landmarks fields of view.
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Autonomous robot for measurement of enclosed areas
KLUGER, Ondřej
The bachelor thesis deals with creating of mobile robotic device for measurement of the enclosed space. This work describes the components of a mobile robot and their function. Furthermore, the work focuses on the di erent types of mobile robots chassis and their suitability for a particular application.
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Mobile Robot Tracking Using Image Processing
Krejsa, Jiří ; Věchet, Stanislav ; Ripel, T.
During the evaluation of autonomous mobile robot navigation routines the determination of true robot position on its track is essential. The paper presents simple yet reliable method of tracking robot position using processing of images acquired from the devices positioned above the operation space. The method consists of two steps for each image: detection of the robot in image space and transfer of its coordinates to operation space.
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Mobile robot motion planner via neural network
Krejsa, Jiří ; Věchet, Stanislav
Motion planning is essential for mobile robot successful navigation. There are many algorithms for motion planning under various constraints. However, in some cases the human can still do a better job, therefore it would be advantageous to create a planner based on data gathered from the robot simulation when humans do the planning. The paper presents the method of using the neural network to transfer the previously gained knowledge into the machine learning based planner. In particular the neural network task is to mimic the planner based on finite state machine. The tests proved that neural network can successfully learn to navigate in constrained environment.
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Nadřízený software pro autonomního závodního robota
Krejsa, Jiří ; Věchet, Stanislav ; Ondroušek, V.
The paper describes the high level software issues in the task of autonomous robot driving on the park pavement. The task in question is to use the sensor data in order to autonomously navigate on the path given in predefined map. The paper gives detail information on the development of software tools for the task and our experience with different ways of sensors data acquisition.
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Markovská lokalizace pro mobilní roboty: simulace a experiment
Krejsa, Jiří ; Věchet, S.
Summary: Localization of the robot is a task of estimating robot position in known environment from sensor observation. The paper describes basic principles of Markov localization technique, succesfully used for localization task. Method is robust against sensor errors and can deal with global uncertainty when robot position is completely unknown. Both simulation and experimental verification of method usability are included.
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