MOBILE ROBOT FOR NAGIVATION AND OCCUPANCY GRID MAPPING

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The aim of this thesis to implement a mobile robot to deliver packages in an enclosed space: remotely to a recipient. This can be applied in various fields such as health care systems in hospitals, transportation and delivery of goods and packages. The robot uses Extended Kalman Filter for sensor fusion. Bayes Theorem was used to update the cells in the occupancy grid map made in real time Simultaneous Localization and Mapping. Bresenham algorithm acts as a checker between the robot and obstacles to detect the presence of free space that the bayes theorem updates with log-odds. The navigation uses frontier based as the robot explore the environment while performing SLAM. The navigation used is after the map has been built is DWA

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Kulcsszavak
Sensor Fusion, Extended Kalman Filter, Bayes Filter, Occupancy Grid Map
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