Abstract: A method and a system for avoiding collision of an object with a work tool coupled to a work machine. The method comprising generating an object signal by an object detector, monitoring the object signal in real-time by a processor, processing the object signal to detect an object at least partially buried in the ground surface, determining a distance between the object and a distance threshold, and sending by a controller a control signal to one or more of a machine control system and a work tool control system to modify one or more of a movement of the work tool or the work machine based on the object reaching the distance threshold.

Abstract: Systems and methods are described for identifying a behavior of a machine. A computer system receives a signal indicative of operation of a field machine and applies a deep learning algorithm to identify a pattern in a collection of signals stored on a computer-readable memory. The collection of signals includes the received signal indicative of operation of the field machine and other signals. A series of targeted tests are performed using a test machine while monitoring a signal indicative of operation of the test machine. A behavior is identified during the series of targeted tests that produces a signal that matches the pattern identified by the deep learning algorithm. An occurrence of the behavior is then automatically identified in the field machine in response to detecting the pattern in the received signal indicative of operation of the field machine.

Abstract: A method of operating a work vehicle at a work area and a work area monitoring system for a work vehicle are provided. The method includes monitoring a target area in the work area and activating a response on the work vehicle directed toward the target area upon satisfaction of a work area condition in the work area.

Abstract: A pattern recognition system receives an image captured by an image capture device, of an operator and the operator is identified. Operator information is accessed, based upon the identified operator, and a control signal is generated to control a mobile machine, based upon the operator information.

Abstract: A method and a system for avoiding collision of an object with a work tool coupled to a work machine. The method comprising generating an object signal by an object detector, monitoring the object signal in real-time by a processor, processing the object signal to detect an object at least partially buried in the ground surface, determining a distance between the object and a distance threshold, and sending by a controller a control signal to one or more of a machine control system and a work tool control system to modify one or more of a movement of the work tool or the work machine based on the object reaching the distance threshold.

Abstract: A smart attachment, or more particularly a wireless beacon for coupling with at least one of an attachment and a work vehicle that operates in rugged environments. The beacon comprises a cylindrical housing with a proximal surface and a distal surface coupled with a fastener. This beacon may further comprise a power source, a printed circuit board, an antenna, and an accelerometer, all located within the cylindrical housing.

Abstract: A mobile construction machine detects a speech processing trigger. It then performs speech processing (such as speech recognition and natural language understanding, speech synthesis, etc.) based on the detected speech processing trigger, to generate a speech processing result. A control signal generator generates control signals based on the speech processing result. The control signals can be used to control the mobile construction machine, to control another mobile construction machine, to provide information to a remote server location, or to aggregate information from multiple remote server locations.

Abstract: A pattern recognition system receives an image captured by an image capture device, of an operator and the operator is identified. Operator information is accessed, based upon the identified operator, and a control signal is generated to control a mobile machine, based upon the operator information.

Abstract: A pattern recognition system receives an image captured by an image capture device, of an operator and the operator is identified. Operator information is accessed, based upon the identified operator, and a control signal is generated to control a mobile machine, based upon the operator information.

Abstract: Systems and methods are described for identifying a behavior of a machine. A computer system receives a signal indicative of operation of a field machine and applies a deep learning algorithm to identify a pattern in a collection of signals stored on a computer-readable memory. The collection of signals includes the received signal indicative of operation of the field machine and other signals. A series of targeted tests are performed using a test machine while monitoring a signal indicative of operation of the test machine. A behavior is identified during the series of targeted tests that produces a signal that matches the pattern identified by the deep learning algorithm. An occurrence of the behavior is then automatically identified in the field machine in response to detecting the pattern in the received signal indicative of operation of the field machine.

Abstract: A pattern recognition system receives an image captured by an image capture device, of an operator and the operator is identified. Operator information is accessed, based upon the identified operator, and a control signal is generated to control a mobile machine, based upon the operator information.

Abstract: A system for managing material loading is disclosed herein. The system comprising a sensor arranged on or proximate a material loading machine that is configured to measure a weight of the material loading machine. A transmitting device communicatively coupled to the sensor that is configured to receive and transmit the measured weight to an electronic data processor. An electronic data processor coupled to each of the sensor and the transmitting device. The electronic data processor is configured to compute a material weight based on the measured weight of the material loading machine and generate an alert for display on a user interface when the material weight exceeds a predetermined threshold.

Abstract: A mobile construction machine detects a speech processing trigger. It then performs speech processing (such as speech recognition and natural language understanding, speech synthesis, etc.) based on the detected speech processing trigger, to generate a speech processing result. A control signal generator generates control signals based on the speech processing result. The control signals can be used to control the mobile construction machine, to control another mobile construction machine, to provide information to a remote server location, or to aggregate information from multiple remote server locations.

Abstract: A mobile construction machine detects a speech processing trigger. It then performs speech processing (such as speech recognition and natural language understanding, speech synthesis, etc.) based on the detected speech processing trigger, to generate a speech processing result. A control signal generator generates control signals based on the speech processing result. The control signals can be used to control the mobile construction machine, to control another mobile construction machine, to provide information to a remote server location, or to aggregate information from multiple remote server locations.

Abstract: A mobile construction machine detects a speech processing trigger. It then performs speech processing (such as speech recognition and natural language understanding, speech synthesis, etc.) based on the detected speech processing trigger, to generate a speech processing result. A control signal generator generates control signals based on the speech processing result. The control signals can be used to control the mobile construction machine, to control another mobile construction machine, to provide information to a remote server location, or to aggregate information from multiple remote server locations.

Abstract: A remote start system for a work vehicle includes a communication unit configured to receive a remote start input signal; optical sensors providing a first image of the work vehicle or work vehicle environment; and a controller including at least a start module and a verification module. The start module is configured to generate a verification request in response to the remote start input signal. In response to the verification request, the verification module is configured to confirm that the first image satisfies a verification condition and to generate a verification confirmation when the first image satisfies the verification condition. The start module is configured to generate a start command in response to the verification confirmation. The remote start system further includes a starter device coupled to the controller and configured to energize a prime mover of the work vehicle upon receipt of the start command from the controller.

Abstract: A remote start system for a work vehicle includes a communication unit configured to receive a remote start input signal; optical sensors providing a first image of the work vehicle or work vehicle environment; and a controller including at least a start module and a verification module. The start module is configured to generate a verification request in response to the remote start input signal. In response to the verification request, the verification module is configured to confirm that the first image satisfies a verification condition and to generate a verification confirmation when the first image satisfies the verification condition. The start module is configured to generate a start command in response to the verification confirmation. The remote start system further includes a starter device coupled to the controller and configured to energize a prime mover of the work vehicle upon receipt of the start command from the controller.

Abstract: A smart attachment, or more particularly a wireless beacon for coupling with at least one of an attachment and a work vehicle that operates in rugged environments. The beacon comprises a cylindrical housing with a proximal surface and a distal surface coupled with a fastener. This beacon may further comprise a power source, a printed circuit board, an antenna, and an accelerometer, all located within the cylindrical housing.

Abstract: An idle state determination system and method are disclosed for a work vehicle having an engine and at least one movable work implement. The movable work implement includes a load bin. The idle state determination system includes a source of work vehicle data that indicates one or more operational parameters of the work vehicle, including at least a speed, a state of an engine and a position of the load bin. The idle state determination system including a source of idle state classifications that include a plurality of idle states associated with the work vehicle, and the plurality of idle states including at least a waiting idle state and a loading idle state. The idle state determination system includes a controller that processes the work vehicle data to determine an idle state of the work vehicle. The controller classifies the idle state as one of the plurality of idle states.

Abstract: A coordinated control method and system for a work vehicle having a primary implement and a secondary implement and one or more controllers. The controller(s) receive a primary implement position input, which is used to generate a primary implement control command to drive one or more primary actuators to position the primary implement. The controller(s) generate a secondary implement control command that is coordinated with the primary implement position input to drive one or more secondary actuators to position the secondary implement in a relative orientation with respect to an orientation of the primary implement resulting from the primary implement control command.