Archive for November, 2010

22 Nov

Tsukuba Challenge

Posted by fahmifahim in Research & Activity. Tagged: .

Tsukuba Challenge [ Real World Robot Challenge (RWRC) ] is a competition of autonomous mobile robot run in real environment (Tsukuba Center Park). The competition is not about how fast the robot can reach the goal, but how the robot can interact with surrounding environment.

Me and my Lab were joined the competition.
Team number 17.
Robot name = MG10
Gunma University feat Mitsuba, Inc.

MG10
MG10. Intel inside! ^_^

Controller Board
Micro-controller, etc

Sensor :
– Stereo Camera (rgb image)
– Wheel encoder (odometry data)
– Laser Range Finder (obstacle detection)

Autonomous navigation system:
– SURF based image recognition
– HOUGH transform
– Line detection
– Sky detection
– Triangle detection
– Tile pattern recognition

Final Round @ Tsukuba Challenge 2010 (19th November 2010)

Project member :
-Shioya Toshiaki (Phd. student)
-Tsunoda Yuuki (Master student)
-Hirano Yuuta (Master student)
-Dzulfahmi (Bachelor student)
-Kodaira Hiroyuki (Bachelor student)
-Ohta Naoya (Professor)

And yup, I recorded the video when MG10 was in action. ^_^

First Day

Final Round

8 Nov

SURF-based Image Recognition

Posted by fahmifahim in Research & Activity. Tagged: , .

Here are the steps :

1. Compute the gray-scale and calculate the SURF features from the model image

2. Turn on the camera and get the real-time input image. Convert each frame to gray-scale

3. Compute the SURF features of the gray-scale camera frame

4. At this step, we want to compare between “model image” and “input image” (camera frame).
For all features of the model, for all features of the camera frame, determine if they represent the same point (calculation of their distance and thresholding) ;

5. Once we have obtained the pairs of associated points, we determine the homography matching all these pairs (using RANSAC or least median squares algorithm) ;

6. Drawing of the projection of the input frame in the illustration frame using this homography.

reference : http://wn.com/realtime_sift_tracking

Application in outdoor visual navigation:

SIFT implementation in OpenCV 2.4

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