TY - GEN
T1 - Localizing Pipe inspection robot using visual odometry
AU - Habibi Aghdam, Hamed
AU - Kadir, Herdawatie Abdul
AU - Arshad, Mohd Rizal
AU - Zaman, Munir
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/3/30
Y1 - 2014/3/30
N2 - There is a special type of concrete pipe beneath the roads in Malaysia which is called culvert. Detecting the place of damages in these pipes is important for maintenance operations. Pipe inspection robots are one of the most reliable ways to achieve this goal. Because of the wheel slippage, low speed motion and dynamic changes in kinematic of the robot, the INS and wheel encoder methods are not accurate enough for localizing the robot inside a culvert. In this paper, we propose a solution based on monocular visual odometry. We show that although the surface of the culvert is not flat, nevertheless, by selecting an appropriate camera the optical flow of the pixels inside a small area near the center of the image is almost equal and for this reason the 3D motion of the robot can be estimated using the derivative of camera parameters. The experimental result shows this method is reliable and can be successfully used for localizing the robot inside the culverts.
AB - There is a special type of concrete pipe beneath the roads in Malaysia which is called culvert. Detecting the place of damages in these pipes is important for maintenance operations. Pipe inspection robots are one of the most reliable ways to achieve this goal. Because of the wheel slippage, low speed motion and dynamic changes in kinematic of the robot, the INS and wheel encoder methods are not accurate enough for localizing the robot inside a culvert. In this paper, we propose a solution based on monocular visual odometry. We show that although the surface of the culvert is not flat, nevertheless, by selecting an appropriate camera the optical flow of the pixels inside a small area near the center of the image is almost equal and for this reason the 3D motion of the robot can be estimated using the derivative of camera parameters. The experimental result shows this method is reliable and can be successfully used for localizing the robot inside the culverts.
KW - features detection
KW - inspection robot
KW - pipe damage
KW - Visual odometry
UR - http://www.scopus.com/inward/record.url?scp=84946690239&partnerID=8YFLogxK
U2 - 10.1109/ICCSCE.2014.7072724
DO - 10.1109/ICCSCE.2014.7072724
M3 - Conference Proceeding
AN - SCOPUS:84946690239
T3 - Proceedings - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014
SP - 245
EP - 250
BT - Proceedings - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2014
Y2 - 28 November 2014 through 30 November 2014
ER -