Well functioning water networks are essential to the sustainability of a community. Large transmission and distribution water mains are often the most sensitive components of these networks since their failure can be catastrophic. Furthermore, due to the high cost of these pipes, the system does not usually provide redundancy to enable decommission for maintenance and rehabilitation. Hence, fai...

We present a vision-based mapping and localization system for operations in pipes such as those found in Liquified Natural Gas (LNG) production. A forward facing, fisheye camera mounted on a prototype robot collects imagery as it is tele-operated through a pipe network. The images are processed offline to estimate camera pose and sparse scene structure where the results can be used to generate ...

Pipe robots can perform inspection tasks to alleviate the damage caused by the pipe problems. Usually, the pipe robots carry batteries or use a power cable draining power from a vehicle that has many equipments for exploration. Nevertheless, the energy is limited for the whole inspection task and cannot keep the inspection time too long. In this paper, we use the total input energy as the cost ...

With the rapid increase in oil and gas consumption in the world’s energy consumption structure, the pace of global oil–gas pipeline construction has accelerated. Pipeline accidents that cause huge economic losses occur frequently, so inspection and maintenance of oil and gas pipelines have become critical issues. This paper presents a helical-contact deformation measuring method based on a mult...

This paper describes development of a three somites earthworm type mobile inspection robot which is able to move in long pipes. We have many small diameter pipes which are gas or water pipes for individual or corporate houses and boilers or hot water pipes for industries. They are settled in the ground horizontally or in the narrow spaces vertically and some of them are covered by casings or ha...

Convolutional neural networks (CNNs) impose constraints on the weights, and the connectivity of a standard neural network, providing a framework well suited to the processing of spatially or temporally distributed data. Although CNNs have been applied to face and character recognition, they have still received relatively little attention. The present paper applies the CNN architecture to an art...