Redzone Robotics, Inc.

Jar Scientific LLC

Clearobject Corporation

Justin Starr

Todd Kueny

Foster J Salotti

Galin Konakchiev

Thorin Tobiassen

Nate Alford

Mark Jordan

Ashish Basuray

Jason Mizgorski

Roman Kazantsev

John Lettman

Timothy Renton

Antony Van Iersel

Randolf Reiss

Tim Gruenhagen

Chase Weaver

Derek Bleyle

Jordan Himes

Charles Pulaski

Christopher White

Anthony Van Iersel

Antony Van Lersel

A cloud server has memory for storing computer readable instructions and a processor for executing the computer readable instruction. A pipe inspection video is received for storage in a video storage container. A plurality of frames is extracted from the pipe inspection video. A plurality of receiver containers is formed to perform artificial intelligence operations the plurality of frames in parallel. The plurality of frames is sent to the plurality of receiver containers to obtain metrics relating to the pipe inspection video. The plurality of frames is returned to the video storage container. The plurality of frames is compiled into a processed pipe inspection video.

Pipe inspection video processing system

An example provides a method, including: obtaining, using one or more sensor systems, sensor data for one or more persons in an environment comprising machinery; analyzing, using a processor, the sensor data using a trained model to identify the one or more persons and an associated time series of actions; determining, using the associated time series of actions, if the one or more persons are engaging in behavior indicative of an unsafe practice; and thereafter presenting safety information to a visual display system, connected software system or other decision support tool.

Computer-vision based workplace safety

An embodiment provides unmanned aerial vehicles (UAVs) for infrastructure surveillance and monitoring. One example includes monitoring power grid components such as high voltage power lines. The UAVs may coordinate, for example using swarm behavior, and be controlled via a platform system. Other embodiments are described and claimed.

Cooperative unmanned autonomous aerial vehicles for power grid inspection and management

A self-propelled device is disclosed to recognize objects, possess objects, and transport objects to a new location. A method is disclosed to use the device to transport objects in environments dangerous to humans. Other example embodiments are described and claimed.

Autonomous object relocation robot

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

An embodiment provides a method, including: obtaining, from a multi-sensor pipe inspection robot that traverses through the interior of a pipe, two or more sets of condition assessment data for the interior of the pipe collected during a single pass through the interior of the pipe; the two or more sets of condition assessment data comprising a first data type obtained using a first sensor type and a second data type obtained using a second sensor type; combining, using a processor, two or more image processing techniques to adjust imaging of a pipe feature; and forming, using the processor, an image of the interior of the pipe using the two or more image processing techniques. Other embodiments are described and claimed.

Image processing techniques for multi-sensor inspection of pipe interiors

An embodiment provides a method including obtaining, using a camera system, imagery of one or more individuals in an environment; analyzing, using a processor, the individual data using a trained model to identify individuals and recognize gestures that are indicative of sickness behavior; presenting, using a display device, information about individuals that have displayed sickness behavior above a calculated threshold.

Rapid illness screening of a population using computer vision and multispectral data

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.

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.

Growing community of inventors

Baden, PA, United States of America

Justin Starr