ICRA 2011 Paper Abstract


Paper WeA205.1

Hansen, Peter (Carnegie Mellon University in Qatar), Alismail, Hatem (Carnegie Mellon University), Rander, Peter (Carnegie Mellon University), Browning, Brett (Carnegie Mellon University)

Monocular Visual Odometry for Robot Localization in LNG Pipes

Scheduled for presentation during the Regular Sessions "SLAM II" (WeA205), Wednesday, May 11, 2011, 10:05−10:20, Room 3G

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on July 14, 2020

Keywords SLAM, Robotics in Hazardous Fields, Mapping


Regular inspection for corrosion of the pipes used in Liquified Natural Gas (LNG) processing facilities is critical for safety. We argue that a visual perception system equipped on a pipe crawling robot can improve on existing techniques (Magnetic Flux Leakage, radiography, ultrasound) by producing high resolution registered appearance maps of the internal surface. To achieve this capability, it is necessary to estimate the pose of sensors as the robot traverses the pipes. We have explored two monocular visual odometry algorithms (dense and sparse) that can be used to estimate sensor pose. Both algorithms use a single easily made measurement of the scene structure to resolve the monocular scale ambiguity in their visual odometry estimates. We have obtained pose estimates using these algorithms with image sequences captured from cameras mounted on different robots as they moved through two pipes having diameters of 152mm (6'') and 406mm (16''), and lengths of 6 and 4 meters respectively. Accurate pose estimates were obtained whose errors were consistently less than 1 percent for distance traveled down the pipe.



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