A power machine can include operator input devices and a control system configured to command movement of actuators based on operator inputs received from the operator input devices. Movement of one or more of the actuators can be commanded based on input at one or more of the operator input devices and a response curve selected from a plurality of different response curves. Movement of one or more of the actuators can be based on a selected control mode for the power machine that corresponds to a selected control-function mapping of the operator input devices to the one or more actuators. A lift arm can be variously controlled to execute automatic or other operations. An excavator can be operated in a sustained-speed travel mode. Actuation of a bucket or other implement can be implemented based on signals from a material sensor.

Disclosed is an adaptive control method applicable to an excavator. The adaptive control method includes: acquiring detection parameters of the excavator, the detection parameters comprising a displacement of an electric control handle of the excavator and angle information of the excavator; identifying a current working condition of the excavator based on the detection parameters; and adjusting control parameters of the excavator based on the current working condition. According to the adaptive control method provided by the present disclosure, the current working condition is identified by using the displacement of the electric control handle and the angle information of the excavator, and then the control parameters of the excavator are adjusted based on the current working condition, so that the control parameters are automatically adjusted with change of the current working condition, which improves control efficiency of the excavator.

A device may receive machine data indicating a pose of one or more components of a machine. The machine data may be generated based on first data from one or more first sensor devices associated with the machine. The device may generate validation data to validate the machine data. The validation data may be generated based on second data from a second set of sensor devices. The device may perform a comparison of the machine data and the validation data and determine, based the comparison, whether the machine data is validated or not validated. The device may selectively control an operation of the machine based on the machine data. Based on determining that the machine data is validated, the operation may be controlled based on the machine data. The operation may be controlled without the machine data based on determining that the machine data is not validated.

A machine control system can store model weights determined via machine learning using a training dataset correlating preset hydraulic valve displacements to measured movement parameters of a machine component. The machine control system can receive an input command for the component and machine state data from machine sensors. A control mapping model can use the model weights to map a combination of the input command and the machine state data into a predicted displacement of the hydraulic valve that causes movement of the component in response to the input command.

Provided is a work machine and the like that can reduce the possibility of contact with an unmanned aircraft flying around. The degree of possibility of contact between a working mechanism (140) and an unmanned aircraft (40) is recognized on the basis of the relative position of the unmanned aircraft (40) with reference to the working mechanism (140). If it is recognized that the contact possibility is high, then the operation mode of at least one of a lower traveling body (110), an upper pivoting body (120), and the working mechanism (140) is controlled so as to reduce the contact possibility.

A work machine includes a mainframe, a boom moveable relative to the mainframe, a work implement coupled to and moveable relative to the boom. The work machine further includes a work-implement operator control configured to transmit a signal indicative of a work-implement movement command, a boom operator control configured to transmit a signal indicative of a boom movement command, and a boom sensor configured to detect a movement of the boom and transmit a signal indicative of the detected movement of the boom. The work implement further includes a controller configured to receive signals from the work-implement operator control, the boom operator control, and the boom sensor. The controller is further configured transmit a signal to cause movement the work implement relative to the boom based on the detected movement of the boom and the work-implement movement command.

A camera captures an image of a region including at least a portion of an operating member and generates image data indicative of the image. A controller acquires the image data from the camera. The controller determines whether an operation of the operating member by an operator is an intentional operation or an unintentional operation based on the image. When the operation of the operating member by the operator is determined to be the intentional operation, the controller controls a work machine according to the operation of the operating member. When the operation of the operating member by the operator is determined to be the unintentional operation, the controller invalidates the operation of the operating member.

Systems and methods for determining a swing angle of a swing boom of a vehicle are provided. Sensor data is received from sensors disposed on a swing boom and a body of a vehicle. It is determined whether the swing boom is static or moving relative to the body based on the sensor data. In response to determining that the swing boom is static, the received sensor data is corrected based on an observed swing angle and an estimated swing angle is calculated based on the corrected sensor data. In response to determining that the swing boom is moving, the estimated swing angle is calculated based on the received sensor data. The estimated swing angle is output.

A work equipment for controllably performing work, includes: a work mechanism; a touch-sensitive device configured to output a desired position signal corresponding to a desired position of the work mechanism, the touch-sensitive device selectively operatively including a virtual mechanical control associated with producing the desired position signal; and a controller operatively coupled to the touch-sensitive device and the work mechanism, the controller configured to output an adjustment signal to the work mechanism to adjust an actual position of the work mechanism based at least partially on the desired position signal, the touch-sensitive device being configured to output the desired position signal to the controller when at least one control object is moved along the touch-sensitive device with respect to the virtual mechanical control in a manner that mimics operating a mechanical control.

Methods and systems for adjusting operating parameters of a machine in anticipation of a transition from a current operational state to a predicted subsequent operational state. An electronic controller receives a data stream indicative of actuator settings, sensor outputs, and/or operator control settings and applies a pattern detection AI that is configured to determine a current operational state of the machine based on patterns detected in the data stream. The controller then applies a reinforcement learning AI that is configured to produce as an output one or more target operating parameters based at least in part on a predicted subsequent operational state of the machine. The one or more target operating parameters are applied to the machine and at least one performance metric of the machine is monitored. The reinforcement learning Ai is retrained based at least in part on the monitored performance metric(s).