General Electric Company

Transportation IP Holdings, LLC

Ge Global Sourcing LLC

Baker Hughes Holdings LLC

Charles Burton Theurer

Huan Tan

Balajee Kannan

John Michael Lizzi

Romano Patrick

Douglas Roy Forman

Brandon Stephen Good

Shaopeng Liu

Omar Al Assad

Shiraj Sen

Yonatan Gefen

Michael Christopher Domke

Arpit Jain

Mauricio Castillo-Effen

Jason Howard Messinger

Tai-Peng Tian

Scott Leo Sbihli

Ghulam Ali Baloch

Robert Lee Wallace

Robert Carroll Ward

Vrinda Rajiv

Thomas Eldred Lambdin

Bradford Wayne Miller

Viktor Holovashchenko

Michael Adam Kinstrey

Kirk Lars Bruns

Judith Ann Guzzo

Sekhar Soorianarayanan

Todd William Danko

Li Zhang

Guiju Song

Shubao Liu

Steven Robert Gray

Todd Franklin Scarola

Shuai Li

Pramod Sharma

David Grey Smith

Frederick Wilson Wheeler

Joseph James Salvo

John William Carbone

Patricia Denise Mackenzie

Francois Xavier De Fromont

Eric Michael Gros

John Robert Hoare

Susan Montagna

Radislav Alexandrovich Potyrailo

Anil Raj Duggal

Mark Bradshaw Kraeling

Yizhen Lin

Deepak Trivedi

Hongyi Zhou

Kareem Sherif Aggour

Benjamin Edward Beckmann

Lynn Ann DeRose

Yakov Polishchuk

Yang Zhao

Ching-Ling Huang

Roberto Silveira Silva Filho

Andrew J Calver

Justin Despenza McHugh

Raju Venkataramana

Bernhard Joseph Scholz

Daniel John Messier

Alex Tepper

Joseph Edward Jesson

Kevin Chean

Ana Dasilva

Charles Robert Gilman

Patrick Anthony Montelo

Roman Brusilovsky

Michael VanderLinden

Norman Wellings

Mark Bachman

Francis Christopher Hann

A control system includes a task manager that can determine capability requirements to perform a task on the target object. The task has an associated series of sub-tasks, with the sub-tasks having one or more capability requirements. The task manager selects and assigns a first sequence of sub-tasks to a first robotic machine that has a first set of capabilities and operates according to a first mode of operation. The task manager selects and assigns a second sequence of sub-tasks to a second robotic machine that has a second set of capabilities and operates according to a second mode of operation. The task manager selects the first robotic machine based on the first set of capabilities and the first mode of operation of the first robotic machine, and selects the second robotic machine based on the second set of capabilities and the second mode of operation.

Control system with task manager

According to some embodiments, an available algorithm data store may contain information about a pool of available algorithms. An algorithm selection platform coupled to the available algorithm data store may access the information about the pool of available algorithms and compare the information about each of the pool of available algorithms with at least one requirement associated with the current algorithm executing in the real environment. The algorithm selection platform may then automatically determine algorithm execution context information and, based on said comparison and the algorithm execution context information, select at least one of the pool of available algorithms as a potential replacement algorithm. An indication of the selected at least one potential replacement algorithm may then be transmitted (e.g., to be evaluated in a shadow environment by an algorithm evaluation platform).

Potential replacement algorithm selection based on algorithm execution context information

A system includes a robotic vehicle having a propulsion and a manipulator configured to perform designated tasks. The system also including a local controller disposed onboard the robotic vehicle and configured to receive input signals from an off-board controller. Responsive to receiving an input signal for moving in an autonomous mode, the local controller is configured to move the robotic vehicle toward one of the different final destinations by autonomously and iteratively determining a series of waypoints until the robotic vehicle has reached the one final destination. For each iteration, the local controller is configured to determine a next waypoint between a current location of the robotic vehicle and the final destination, determine movement limitations of the robotic vehicle, and generate control signals in accordance with the movement limitations.

Control system and method for robotic motion planning and control

A system includes a first robotic machine having a first set of capabilities for interacting with a target object on stationary equipment; a second robotic machine having a second set of capabilities for interacting with the target object; and a task manager that can determine capability requirements to perform a task on the target object. The task has an associated series of sub-tasks. The task manager can assign a first sequence of sub-tasks for performance by the first robotic machine based on the first set of capabilities and a second sequence of sub-tasks for performance by the second robotic machine based on the second set of capabilities. The first and second robotic machines can coordinate performance of the first sequence of sub-tasks by the first robotic machine with performance of the second sequence of sub-tasks by the second robotic machine to accomplish the task.

A robotic system includes a controller configured to obtain image data from one or more optical sensors and to determine one or more of a location and/or pose of a vehicle component based on the image data. The controller also is configured to determine a model of an external environment of the robotic system based on the image data and to determine tasks to be performed by components of the robotic system to perform maintenance on the vehicle component. The controller also is configured to assign the tasks to the components of the robotic system and to communicate control signals to the components of the robotic system to autonomously control the robotic system to perform the maintenance on the vehicle component.

Integrated robotic system and method for autonomous vehicle maintenance

Methods and apparatus disclosed herein autonomously evaluate replacement algorithms. An example system associated with a live environment executing a current algorithm includes at least one memory, instructions, and processor circuitry to execute the instructions to manage execution of the current algorithm in the live environment, the live environment associated with a deployment platform, and manage, based on receipt of at least one potential replacement algorithm, a shadow environment causes execution of the at least one potential replacement algorithm in the shadow environment, the shadow environment instantiated separately from the live environment, the shadow environment utilizes data from the live environment during execution of the at least one potential replacement algorithm in the shadow environment.

Performance manager to autonomously evaluate replacement algorithms

An algorithm data store may contain information about a pool of available algorithms (e.g., to improve operation of an industrial asset). A deployment platform may be implemented in an edge portion at an industrial site associated with a live environment executing a current algorithm. A lifecycle manager of the deployment platform may manage execution of the current algorithm in the live environment creating source data. A performance manager may receive an indication of a selected at least one potential replacement algorithm from the pool of available algorithms and manage execution of the at least one potential replacement algorithm in a shadow environment using the source data. The performance manager may then report performance information associated with the at least one potential replacement algorithm. When appropriate, the potential replacement algorithm may replace the current algorithm.

A system includes a first robotic machine having a first set of capabilities for interacting with a target object; a second robotic machine having a second set of capabilities for interacting with the target object; and a task manager that can determine capability requirements to perform a task on the target object. The task has an associated series of sub-tasks. The task manager can assign a first sequence of sub-tasks for performance by the first robotic machine based on the first set of capabilities and a second sequence of sub-tasks for performance by the second robotic machine based on the second set of capabilities. The first and second robotic machines can coordinate performance of the first sequence of sub-tasks by the first robotic machine with performance of the second sequence of sub-tasks by the second robotic machine to accomplish the task.

A method including positioning a modular robotic component proximate an area of interest on a surface of a wind turbine. The modular robotic component including a plurality of modules that perform a plurality of tasks. The method further including inspecting the area of interest with the modular robotic component for an indication requiring at least one of repair or upgrade and operating the modular robotic component to perform the plurality of tasks sequentially as the modular robotic component moves along the surface of the wind turbine. A modular robotic component and system including the modular robotic component are disclosed.

System and method for wind blade inspection, repair and upgrade

Systems and methods for facilitating proximity detection and location tracking using a hub or bridge are disclosed. An example apparatus is to receive a message from a beacon at a second location within a proximity area of the apparatus, the message indicative of the second location and identifying the beacon; and relay the message to a location server to determine asset location.

Hardware system for active RFID identification and location tracking

Methods, apparatus, systems and articles of manufacture are disclosed to facilitate proximity detection and location tracking. An example method includes receiving messages collected by a badge in an environment, the messages including signal strength and a timestamp. The example method also includes assigning a location in the environment to the badge based on a first subset of the messages. The example method also includes identifying an asset in a second subset of the messages. The example method also includes updating a current location associated with the asset based on a relative proximity of the asset to the badge, wherein the current location corresponds to a first time and the updated location corresponds to a second time, and wherein a change in location between the current location and the updated location indicates movement of the asset in the environment.

Methods and apparatus to facilitate proximity detection and location tracking

A sensor calibration system includes a plurality of sensors and a user interface configured to receive user-provided locations of at least two sensors of the plurality of sensors. The sensor calibration system further includes a motorized apparatus including a drive system, at least one detector, and a localization system. The sensor calibration system further includes a controller communicatively coupled to the user interface and the motorized apparatus. The controller is configured to determine a whether each of at least two sensors is a key sensor based on the user-provided locations. The controller is configured to determine a path for the motorized apparatus based on the user-provided locations. The controller is further configured to determine a position of each sensor based on the location of the motorized apparatus when each sensor is detected by the at least one detector. The controller is further configured to relate the location of the motorized apparatus and the position of each sensor to a common origin.

Systems and methods including motorized apparatus for calibrating sensors

Growing community of inventors

Alplaus, NY, United States of America

Charles Burton Theurer