A novel soft-computing technique to segment satellite images for mobile robot localization and navigation

Date

2007-11-02

Author

DOĞRUER, CAN ULAŞ
Koku, Ahmet Buğra
Dölen, Melik

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

194
views

0
downloads

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 is proposed to segment and convert a satellite image into a digital map for outdoor mobile robot applications.

Subject Keywords

Image segmentation, Mobile robots, Satellite navigation systems, Simultaneous localization and mapping, Robot sensing systems, Intelligent robots, Cities and towns, Image converters, Fuzzy systems, Monte Carlo methods

URI

https://hdl.handle.net/11511/42729

DOI

https://doi.org/10.1109/iros.2007.4399494

Collections

Department of Mechanical Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Global urban localization of an outdoor mobile robot with genetic algorithms DOĞRUER, CAN ULAŞ; Koku, Ahmet Buğra; Dölen, Melik (2008-02-26) The localization of mobile robots has been studied rigorously in the past. However, only a few studies have focused on developing specific Genetic Algorithms (GAs) to address the localization problem effectively. In this study; the global urban localization of an outdoor mobile platform is considered with the utilization of the odometer, the laser-rangeq finder measurements and the digital maps created from the relevant satellite images on the Internet. The localization issue is formulated as a constrained ...
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...
An Implementation of 3D slam with planar segments Turunç, Çağrı; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2012) Localization and mapping are vital capabilities for a mobile robot. These two capabilities strongly depend on each other and simultaneously executing both of these operations is called SLAM (Simultaneous Localization and Mapping). SLAM problem requires the environment to be represented with an abstract mapping model. It is possible to construct a map from point cloud of environment via scanner sensor systems. On the other hand, extracting higher level of features from point clouds and using these extracted ...
Improving the accuracy of a mobile robot for localization and mapping of an unknown environment Gümrükcü, Gülşah; Konukseven, Erhan İlhan; Department of Mechanical Engineering (2003) 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 ...
Global Urban Localization of Outdoor Mobile Robots Using Satellite Images DOĞRUER, CAN ULAŞ; Koku, Ahmet Buğra; Dölen, Melik (2008-09-26) Localization is one of the major research fields in mobile robotics. With the utilization of satellite images and Monte Carlo localization technique, the global localization of an outdoor mobile robot is studied in this paper. The proposed method employs satellite images downloaded from the Internet to localize the robot iteratively. To accomplish this, the proposed method matches the local laser scanner data with the segmented satellite images. Initial test results conducted on the METU campus are found to...

Citation Formats

C. U. DOĞRUER, A. B. Koku, and M. Dölen, “A novel soft-computing technique to segment satellite images for mobile robot localization and navigation,” 2007, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42729.