Development of LIDAR System Using Camera And Laser

Gürkan Küçükyıldız, Suat Karakaya

In this study, the instantaneous distances of the objects in the environment were studied by using camera and laser. In the developed system, a mirror was used to keep the camera and the laser fixed and change the view angle of both. The mirror is integrated into the system to provide a 45o angle to the focus line of the camera. One reducer DC motor is used to rotate the mirror in the system. In this way, the system can receive data at a desired speed and resolution in a 270-degree area. The codes for the system are written in Phyton environment and a development card based on the Atmel Atmega328p processor is used for controlling the DC motor in the system. It is seen that the developed system scans an area of 360o with a resolution of 3.30o within 1.8 seconds.

Image Processing Based Indoor Localization System

Gürkan Küçükyıldız, Suat Karakaya

In this study, image processing based low cost indoor localization system was developed. Image processing algorithm was developed in C++ programming language and Open CV image processing library.  Frames were captured by a USB camera which was designed for operating at 850 nm wave length to eliminate environmental disturbances. A narrow band pass filter was integrated to camera in order to detect retro reflective labels only. Retro reflective labels were placed ceiling of indoor area with pre-determined equal spaced grids. Approximate location of mobile robot was obtained by label identity and exact location of mobile robot was obtained with detected label’s position at image coordinate system. Developed system was tested on a mobile robot platform and it was observed that system is operating successfully in real time.

Encoder-Based Localization, Obstacle Detection on a Mobile Robot Platform

Gürkan Küçükyıldız, Suat Karakaya

In this study, a mobile robot which is sensitive to its environment was developed and the mobile robot was tested in different obstacle conditions. The mobile robot senses the obstacles via a laser range finder(Lidar) sensor mounted on its body. The developed mobile robot has two front wheels which are coupled with two separated DC motors and single caster as rear wheel. Real time location of the mobile robot was handled from the encoders coupled with the front wheels. This location info was plotted on a user interface which was developed in Visual C # 2010 environments. Obstacle and heading direction detection was developed in Visual Basic 6.0 environment.

A Hybrid Indoor Localization System Based on Infra-red Imaging and Odometry

Gürkan Küçükyıldız, Suat Karakaya

In this study, a real-time indoor localization system was developed by using a camera and passive landmarks. A narrow band-pass infra-red (IR) filter was inserted to the back of the camera lens for capturing IR images. The passive landmarks were placed on the ceiling at pre-determined locations and consist of IR retro-reflective tags that have binary coded unique ID’s. An IR projector emits IR rays at the tags on the ceiling. The tags then reflect the rays back to the camera sensor creating a digital image. An image processing algorithm was developed to detect and decode the landmarks in captured images. The proposed algorithm successfully estimates the position and the orientation angle based on relative position and orientation with respect to the detected tags. To further improve the accuracy of the estimates, extended Kalman filter (EKF) was adapted to the measurement algorithm. The proposed method initially estimates the position of a mobile robot based on odometry and kinematic model. EKF was then used to update the estimates given the measurement obtained from the image processing system. Real time experiments were performed to test the performance of the system. The results prove that the proposed indoor localization system can effectively estimate position with an error less than 5cm.

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