Development of a visual object localization module for mobile robots

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 localizing the objects, the module is designed to combine the results of two different techniques. The visual looming technique measures the distance to an object using the change in the size of the object on the image plane. This technique is to be complemented by a variant of the triangulation technique that can locate an object using the eccentricity of the object when viewed from two different points. The module-with the preprocessing algorithm-is being implemented to run in real-time on a mobile robot. Evaluation of the visual localization module is being done in an integrated system introduced in the article. The integrated system creates an environment for real-time evaluation of the module as well as other mapping and navigation algorithms for mobile robots.


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 ...
Şahin, Yiğit; Koku, Ahmet Buğra; Department of Aerospace Engineering (2021-12-29)
An algorithm for visual topological localization and navigation is proposed. Landmark detection and tracking is performed in successive frames to determine angular changes between repetitive and salient features. This angular state is used to generate heading vector which will lead the robot to the target scene. This reactive navigation behavior is aided with localization and path planing algorithms to complete the SLAM capability. Our algorithm is tested in 2 different natural indoor environments. Results ...
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...
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...
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...
Citation Formats
E. Şahin, “Development of a visual object localization module for mobile robots,” 1999, Accessed: 00, 2020. [Online]. Available: