Monocular Visual Odometry for Robot Localization in LNG Pipes
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.
Peter Hansen Hatem Alismail Peter Rander Brett Browning
Qri8 lab,Carnegie Mellon University,Doha,Qatar Robotics Institute/NREC,Carnegie Mellon University,Pittsburgh PA,USA
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3111-3116
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）