Redzone Robotics, Inc.

Galin Konakchiev

Justin Starr

Todd Kueny

Foster J Salotti

Thorin Tobiassen

Nate Alford

Mark Jordan

Jason Mizgorski

John Lettman

Jordan Himes

Charles Pulaski

Christopher White

One aspect provides operating a mobile pipe inspection platform to obtain two or more types of sensor data for the interior of a pipe; analyzing, using a processor, the two or more types of sensor data using a trained model, where the trained model is trained using a dataset including training sensor data of pipe interiors; the analyzing including performing: identifying, using a processor, a pipe feature location using a first type of the two or more types of sensor data; and classifying, using a processor, an identified pipe feature using a second type of the two or more types of sensor data; and thereafter producing, using a processor, an output including an indication of the classified pipe feature. Other aspects are described and claimed.

Underground infrastructure feature identification using multi-sensor inspection data analysis

One embodiment provides a system, including: an inspection platform configured to move through underground infrastructure; an imaging device coupled to the inspection platform; the imaging device comprising a camera housing that arranges an array of four or more cameras in a predetermined configuration; the camera housing comprising a plurality of apertures, wherein each aperture houses a respective camera therein with a viewing axis offset about 30 degrees to about 120 degrees from a viewing axis of an adjacent camera within the array; and circuitry that operates the imaging device to capture a plurality of images using the four or more cameras; where the circuitry captures the plurality of images for a composite image of an interior region of the underground infrastructure, and where the region is larger than a single viewing field of any of the four or more cameras. Other embodiments are described and claimed.

Multiple camera imager for inspection of large diameter pipes, chambers or tunnels

One aspect provides a method, including: obtaining sensor data from a ground penetrating radar (GPR) unit; analyzing, using a processor, the sensor data to detect a first object and a second object, the second object being associated with the first object based on location; identifying, with the processor, an underground pipe feature based on the analyzing; associating a position of the underground pipe feature with a location in a pipe network; selecting a subset of the pipe network including a pipe segment associated with the position of the underground pipe feature; and providing the subset of the pipe network as displayable data to a display device. Other aspects are described and claimed.

Underground infrastructure sensing using unmanned aerial vehicle (UAV)

One embodiment provides a pipe inspection robot, including: a chassis configured to traverse through an interior of a water or sewer pipe; a water quality probe comprising a first end that couples to the chassis and a sensing end distal thereto; an electric motor configured to reposition the sensing end of the water quality probe with respect to the chassis; said electric motor acting to move the sensing end of the water quality probe to reposition the sensing end proximate to fluid containing water located proximate to a bottom part of the chassis; the sensing end configured to contact the fluid containing water for contact sensing of water quality data. Other aspects are described and claimed.

Method and apparatus for robotic, in-pipe water quality testing

An embodiment provides a method of controlling a pipe inspection robot, including: detecting, from a headset, brain activity of a user wearing the headset; binning the brain activity of the user into one of a plurality of different bins; the binning comprising accumulating brain activity values for a period of time to establish a brain activity value for the period of time; determining, using the brain activity value, if a threshold level of brain activity has accumulated over the period of time; after the threshold level has been accumulated, identifying a control action to be sent to the pipe inspection robot based on the brain activity value; and controlling the movement of the pipe inspection robot using a control signal associated with the control action. Other embodiments are described and claimed.

Controlling robot with head mounted controller

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.

One aspect provides a method, including: displaying, at a display screen, an image of an interior of a pipe, the image being obtained using a pipe inspection robot; accessing, using a processor, calibration data associated with the image; receiving, via an input device, user input marking at least a portion of the image; determining, using a processor, quantitative pipe feature data for at least one feature of the pipe using the marking and the calibration data; and providing, based on the determining, data associated with the at least one feature. Other aspects are described and claimed.

Pipe image feature analysis using calibration data

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.

Pipe feature identification using pipe inspection data analysis

One embodiment provides a pipe inspection robot, including: a chassis configured to traverse through an interior of a water or sewer pipe; an extension piece coupled to the chassis; a water quality probe comprising a first end that couples to the extension piece and a sensing end distal thereto; an electric motor configured to reposition the sensing end of the water quality probe with respect to the extension piece; said electric motor acting to rotate the sensing end of the water quality probe to reposition the sensing end proximate to fluid containing water located proximate to a bottom part of the chassis; the sensing end configured to contact the fluid containing water for contact sensing of water quality data. Other aspects are described and claimed.

One embodiment provides a pipe inspection robot, including: a powered track system providing movement to the pipe inspection robot; a sensor component comprising a water quality probe; and a processor; said processor configured to: operate the water quality probe to collect water quality data related to a fluid contained within a pipe; and communicate the water quality data collected over a network connection. Other aspects are described and claimed.

One embodiment provides an apparatus, including: a pipe inspection robot that traverses a pipe; a fetter comprising a water pump; and an intake hose that couples the pump of the jetter to a local water source proximate to the pipe inspection robot. Other aspects are described and claimed.

Mobile jetter and pipe inspection robot

One embodiment provides a method for identifying a target object of a pipe wall, including: positioning a pipe inspection robot within a pipe; emitting, using a terahertz (THz) beam source of the pipe inspection robot, a laser beam towards a target object; receiving, using a THz receiver of the pipe inspection robot, THz data related to the target object; analyzing, using a processor, the THz data; and determining, based on the analyzing, an identity of the object. Other aspects are described and claimed.

Growing community of inventors

Pittsburgh, PA, United States of America

Galin Konakchiev