LPV: LNG Pipe Vision

monocular camera pipe 3d reconstruction our robot in the pipe

Accurate assessment of pipe corrosion rates is critical to the safety and productivity in Liquid Natural Gas (LNG) plants. Due to the growing complexity of LNG plants, safety, the time consuming task of manual pipe inspection, and cost, current inspection techniques can not cover every pipe in the pipe network Often, inspectors resort to extrapolation which predicts corrosion rates instead of acquiring direct estimates. In this work, we investigate the use of computer and machine vision techniques for building accurate 3D models of pipe surface with sub-millimeter accuracy. Specifically, a pipe crawler robot can carry a camera, or a set of cameras, that capture images of the internal pipe surface. Given those images we can to create 3D models that are reliable and repeatable for the task of corrosion inspection and change detection.

Some challenges and research questions we are trying to address include:

  • How to choose and control lighting inside the pipe?
  • What are the best camera systems suited for the task of reliable 3D reconstruction in pipe (monocular, stereo, omnidirectional, a ring of cameras, etc)?
  • How to exploit the known geometry of a pipe to achieve sub-millimeter accuracy (for 3D reconstruction and visual odometry) that might not be possible in general environments?

Keywords: 3D reconstruction, stereo, visual odometry, registration, change detection.

People: Dr. Brett Browning (Robotics Institute), PI, Dr. Peter Rander Co-PI (NREC), Dr. Peter Hansen, Carnegie Mellon Qatar

Visual Odometry and Pose Estimation

visual odometry in Wean hall example error distribution for different pose estimation methods distribution of pose errors Visual odometry (VO), or motion estimation from imagery, has become the method of choice for motion estimation for robots in many situations. The low cost, high information content, and passive nature of cameras make them ideal for a variety of applications. Two main approaches to visual odometry exist: (1) methods that derive from the state estimation (EKF, Particle filters, etc) from robotics and (2) Structure-from-Motion (SFM) based methods common in the computer vision literature. In this work, we are interested in SFM-based methods as they are relatively more extensible and stable.

SFM-based stereo VO pipeline consists of three main steps: (1) feature extraction, 3D triangulation and tracking, (2) pose estimation from tracked features, and (3) non-linear refinement of motion and structure parameters. Pose estimation is at the core of SFM-based VO as pose estimation methods need to tolerate feature tracking and extraction errors. Furthermore, estimated pose needs to be accurate enough for non-linear refinement methods to converge. In this work, we conducted a large empirical study to investigate several classes of pose estimation algorithms, evaluate them on simulated data, as well as indoor and outdoor data set. The aim is give insight into the different algorithms and the main factors that affect the accuracy of pose estimation methods from stereo imagery.

Keywords: Stereo visual odometry, Pose estimation, Perspective-N-Points (PnP), Absolute Orientation (AO)

People: Dr. Brett Browning (Robotics Institute), Dr. Bernardine Dias (Robotics Institute)

Technology for Developing Communities

istep logo literacy tools project screenshot

Despite the importance of literacy to most aspects of life, underserved communities continue to suffer from low literacy rates; especially for globally prevalent languages such as English. In the summer of 2009, I participated in iSTEP (innovative Student Technology ExPerience), TechBridgeWorld summer research internship program. One of iSTEP projects was to create and evaluate culturally-relevant educational technology and games for child literacy. I was the iSTEP 2009 Technical Lead for the Literacy Tools project working with primary school teachers and students at the Mlimani Primary School in Dar es Salaam, Tanzania.

I took the lead on technical development and testing for the project which resulted in an interactive mobile phone game which quizzes students on English grammar and an online Content Authoring Tool which allows teachers to create their own questions and answers for the game. The project has since expanded to other user groups (middle school deaf and hard-of-hearing students, migrant workers and university students) in different countries (the United States, Qatar and Bangladesh, respectively) and has become a program at TechBridgeWorld, where it is formally known as TechCaFE (Technology for Customizable and Fun Education).

Keywords: ICTD, English Literacy, Mobile Phones

People: Rotimi Abimbola, Hatem Alismail, Sarah Belousov, Beatrice Dias, Freddie Dias, M. Bernardine Dias, Imran Fanaswala, Bradley Hall, Daniel Nuffer, Ermine A. Teves, Jessica Thurston, Anthony Velázquez