Improving the accuracy of a mobile robot for localization and mapping of an unknown environment

Gümrükcü, Gülşah
This thesis deals with sensor based motion planning of a mobile robot for localization in an unknown environment. Using the developed algorithm the robot may construct the map (GVG) of any bounded environment, and the minimum distance between any two locations in the mapped environment can be determined. In addition, the accuracy of the robot, facing dead-reckoning error can be improved. With this study, the mobile robot finds the optimum path between any two locations in any bounded environment and traces this path with the highest accuracy.


Development of a visual object localization module for mobile robots
Şahin, Erol (1999-01-01)
Reports preliminary results from the design and implementation of a visual object localization module for mobile robots. The module takes an object-based approach to visual processing and relies on a preprocessing step that segments objects from the image. By tracking the size and the eccentricity of the objects in the image while the robot is moving, the visual object localization module can determine the position of objects relative to the robot using the displacement obtained from its odometry. In locali...
Bilaloğlu, Cem; Turgut, Ali Emre; Şahin, Erol; Department of Mechanical Engineering (2022-1-13)
This thesis introduces Kobot -- an extensible heterogeneous swarm robot platform. Kobot platform uses a common hardware and software architecture based on off-the-shelf components, 3-D printing, and open-source software that evolves with state of the art. Robots built using this common architecture range from wheeled to flying robots and formed a heterogeneous swarm. The common architecture enabled developing and testing systems for the lightweight flying robots on resourceful ground robots. As a result, Ko...
Performance comparison of point and plane features for SLAM /
Yörük, Mücahit; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2014)
Simultaneous Localization and Mapping (SLAM) is an indispensable capability for mobile robots that explore unknown environments. This advanced method is now widely employed since the development of improvements in sensor technology, such as 3D depth cameras. To avoid the risk of the human interaction in dangerous environments, various SLAM algorithms have been developed and proposed in the literature. The aim of this study, is to develop a landmark vector that improves the SLAM performance using the planar ...
A novel soft-computing technique to segment satellite images for mobile robot localization and navigation
DOĞRUER, CAN ULAŞ; Koku, Ahmet Buğra; Dölen, Melik (2007-11-02)
Localization of mobile robots has been studied rigorously in the last decade. A number of successful approaches such as Extended Kalman Filter, Markov Localization, and Monte Carlo Localization assume that the map of the environment is originally presented to the robot. However, an important information package like the map of the environment could not be taken for granted in most realworld problems. In this study, a novel technique composed of a combination of Fuzzy C-Means and Fuzzy Neural Network methods...
Performance Evaluation of the Grid-based FastSLAM in V-RFP Using MATLAB
Azak, Salim (2018-02-24)
This paper presents a Simultaneous Localization and Mapping (SLAM) application that is developed in V-REP robot simulation program by using Grid-Based FastSLAM method. In this work, the SLAM problem in an unknown indoor environment is solved with the Pioneer 3 DX mobile robot equipped with a laser range finder. Control scripts are developed in the Lua and FastSLAM scripts using MATLAB that is linked to the simulation platform by means of the Remote API feature of the V-REP. In order to evaluate of the perfo...
Citation Formats
G. Gümrükcü, “Improving the accuracy of a mobile robot for localization and mapping of an unknown environment,” M.S. - Master of Science, Middle East Technical University, 2003.