Abstract:
One aspect provides a method, including: obtaining sensor data from an unmanned aerial vehicle (UAV); the sensor data comprising data obtained by one or more sensors of the UAV; analyzing, using a processor, the sensor data to detect underground water associated with a pipe; and identifying, with the processor, an underground feature based on the analyzing. Other aspects are described and claimed.
Abstract:
One embodiment provides methods for identifying a target object of a pipe wall, including using a terahertz (THz) beam source of a pipe inspection robot. Another embodiment provides methods of analyzing water quality within a pipe using a pipe inspection robot. Another embodiment provides a mobile jetter in connection with a pipe inspection robot. A further embodiment provides methods of visualizing pipe inspection data, including virtual reality displays. Other aspects are described and claimed.
Abstract:
Systems, methods and. devices for indexing, archiving, analyzing and reporting pipe and other void network data. Specifically, multi-dimensional indexing and correlation of spatial, temporal, feature, environmental, uncertainty and/ or context-based data is synchronized, indexed and analyzed across a wide variety of pipe networks at various times. The present invention preferably includes data represented at several different levels of reference including: referenced to the sensor with which it was collected; referenced to the robot or platform upon which the sensor is attached; and the world. The structure and functionality of the system provides for extensive querying, trouble -shooting and predictive analysis for pipe networks.
Abstract:
Systems, methods and. devices for indexing, archiving, analyzing and reporting pipe and other void network data. Specifically, multi -dimensional indexing and correlation of spatial, temporal, feature, environmental, uncertainty and/ or context -based data is synchronized, indexed and analyzed across a wide variety of pipe networks at various times . The present invention preferably includes data represented at several different levels of reference including: referenced to the sensor with which it was collected; referenced to the robot or platform upon which the sensor is attached; and the world. The structure and functionality of the system provides for extensive querying, trouble -shooting and predictive analysis for pipe networks.
Abstract:
In one example, a method includes combining multi-sensor inspection (MIS) data from sensors of inspection platform(s); using respective metadata to select one or more tools for translating the MSI data into a common file format; applying the one or more tools to the first and second MSI data to obtain respective common data formatted files; and providing, via a cloud computing device, access to the common data formatted files. Other implementations may be described and claimed.
Abstract:
An embodiment provides a method, including: obtaining, from a multi-sensor pipe inspection robot that traverses through the interior of a pipe, sensor data, such as structured laser light sensor data and Light Detection and Ranging (LIDAR) sensor data, for the interior of the pipe; identifying a pipe feature using one or more of the sensor data types; selecting an image processing technique based on the pipe feature identified using a stored association between the pipe feature and an image processing technique; and forming an image of the interior of the pipe by implementing the selected image processing technique. Other embodiments are described and claimed.
Abstract:
One aspect provides a method, including: operating a mobile pipe inspection platform to obtain sensor data for the interior of a pipe; analyzing, using a processor, the sensor data using a trained model, where the trained model is trained using a dataset including sensor data of pipe interiors and one or more of: metadata identifying pipe feature locations contained within the sensor data of the dataset and metadata classifying pipe features contained within the sensor data of the dataset; performing one or more of: identifying, using a processor, a pipe feature location within the sensor data; and classifying, using a processor, a pipe feature of the sensor data; and thereafter producing, using a processor, an output including one or more of an indication of the identifying and an indication of the classifying. Other aspects are described and claimed.
Abstract:
Methods and apparatuses for inspecting manholes or other voids and collecting data in a comprehensive, repeatable, and measurable manner. A sensor head is suspended and lowered into a manhole or other void. The sensor head collects data related to the condition of the manhole or void walls, and locations of defects, damage, or lateral pipe openings. The data can then be processed to provide a three-dimensional model of the manhole or void, and can be compared to previous or future data.
Abstract:
An autonomous inspector mobile platform robot that is used to inspect a pipe or network of pipes. The robot includes a locomotion device that enables the device to autonomously progress through the pipe and accurately track its pose and odometry during movement. At the same time, image data is autonomously captured to detail the interior portions of the pipe. Images are taken at periodic intervals using a wide angle lens, and additional video images may be captured at locations of interest. Either onboard or off board the device, each captured image is unwarped (if necessary) and combined with images of adjacent pipe sections to create a complete image of the interior features of the inspected pipe. Optional features include additional sensors and measurement devices, various communications systems to communicate with an end node or the surface, and/or image compression software.
Abstract:
One aspect provides a modular inspection robot for inspecting vertical shafts, chambers or tunnels. An embodiment provides related methods and products. One method includes: capturing, using a plurality of video cameras associated with an infrastructure inspection unit, two or more videos of infrastructure; accessing, using one or more processors, image metadata indicating a mesh of connected vertices based on the two or more videos; selecting, using the one or more processors, image data of frames of the two or more videos for inclusion in an output based on the mesh; and outputting, using the one or more processors, a photo-realistic image of the infrastructure comprising the image data selected. Other examples are described and claimed.