General Electric Company

Transportation IP Holdings, LLC

Ge Global Sourcing LLC

Balajee Kannan

Charles Burton Theurer

Huan Tan

John Michael Lizzi

Romano Patrick

Douglas Roy Forman

Omar Al Assad

Yonatan Gefen

Tai-Peng Tian

Arpit Jain

Weston Blaine Griffin

Yi Xu

Guiju Song

Lynn Ann DeRose

Shiraj Sen

Ghulam Ali Baloch

Ying Mao

Shubao Liu

Viktor Holovashchenko

Shuai Li

Pramod Sharma

Frederick Wilson Wheeler

Mark Bradshaw Kraeling

Mauricio Castillo-Effen

Xianqiao Tong

Michael VanderLinden

Norman Wellings

Mark Bachman

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

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

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.

An approach relates to manipulation of tools or instruments in the performance of a task by a robot. In accordance with this approach, sensor data is acquired and processed to identify a subset of instruments initially susceptible to manipulation. The instruments are then manipulated in the performance of the task based on the processed sensor data.

Method and robotic system for manipulating instruments

The present approach relates to integrated planning of robot navigation and manipulator motion in performing tasks. In particular, as discussed herein sensor information, such as visual information, may be used for the robot to locate a target object when it arrives at a working location. Adjustments may be made based on this information that may include moving the robot and planning a manipulator arm motion.

Architecture and methods for robotic mobile manipulation system

Systems and methods are provided for an automation system. The systems and methods calculate a motion trajectory of a manipulator and an end-effector. The end-effector is configured to grasp a target object. The motion trajectory defines successive positions of the manipulator and the end-effector along a plurality of via-points toward the target object. The systems and methods further acquire force/torque (F/T) data from an F/T sensor associated with the end-effector, and adjusts the motion trajectory based on the F/T data.

Control system and method for applying force to grasp a target object

A robotic system includes one or more optical sensors configured to separately obtain two dimensional (2D) image data and three dimensional (3D) image data of a brake lever of a vehicle, a manipulator arm configured to grasp the brake lever of the vehicle, and a controller configured to compare the 2D image data with the 3D image data to identify one or more of a location or a pose of the brake lever of the vehicle. The controller is configured to control the manipulator arm to move toward, grasp, and actuate the brake lever of the vehicle based on the one or more of the location or the pose of the brake lever.

Multisensory data fusion system and method for autonomous robotic operation

A robot system is provided that includes a base, an articulable arm, a visual acquisition unit, and at least one processor. The articulable arm extends from the base and is configured to be moved toward a target. The visual acquisition unit is mounted to the arm or the base, and acquires environmental information. The at least one processor is operably coupled to the arm and the visual acquisition unit, the at least one processor configured to: generate an environmental model using the environmental information; select, from a plurality of planning schemes, using the environmental model, at least one planning scheme to translate the arm toward the target; plan movement of the arm toward the target using the selected at least one planning scheme; and control movement of the arm toward the target using the at least one selected planning scheme.

Systems and methods for control of robotic manipulation

A locomotive control system may include first and second robotic machines and a task manager. The first and second robotic machines have respective first and second sets of capabilities for interacting with a surrounding environment. The task manager selects the first and second robotic machines from a group to perform a task based on the first and second sets of capabilities of the robotic machines. The task involves manipulating and/or inspecting a target object of a vehicle. The task manager assigns a first sequence of sub-tasks to be performed by the first robotic machine and a second sequence of sub-tasks to be performed by the second robotic machine. The first and second robotic machines are configured to 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.

Vehicle control system with task manager

Control system and method for applying force to grasp a brake lever

A robot system and method are provided that move an articulable arm relative to a target object. Perception information corresponding to a position of the arm relative to the target object is acquired. Movement of the arm is controlled based on the perception information. After movement of the arm, predicted position information representative of a predicted positioning of the arm is provided using the perception information and control signal information. The arm is subsequently controlled using the predicted position information.

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Niskayuna, NY, United States of America

Balajee Kannan