A method of the present disclosure includes (a) retrieving from a memory a plurality of measured values of the factor variable, and a label indicating good or bad of the quality corresponding to each of the plurality of measured values, (b) dividing a factor variable space defined by the factor variable into a plurality of grids by equally dividing a range determined by a maximum value and a minimum value of the plurality of measured values for each factor variable, (c) setting a plurality of candidate areas each of which includes one grid or a plurality of adjacent grids, and deriving, for each of the plurality of candidate areas, a good density based on the label associated with the measured value that is within the candidate area, and (d) selecting one of the plurality of candidate areas as the factor variable area, based on the good density.

A method of the present disclosure includes (a) retrieving from a memory a plurality of measured values of the factor variable, and a label indicating good or bad of the quality corresponding to each of the plurality of measured values, (b) dividing a factor variable space defined by the factor variable into a plurality of grids by equally dividing a range determined by a maximum value and a minimum value of the plurality of measured values for each factor variable, (c) setting a plurality of candidate areas each of which includes one grid or a plurality of adjacent grids, and deriving, for each of the plurality of candidate areas, a good density based on the label associated with the measured value that is within the candidate area, and (d) selecting one of the plurality of candidate areas as the factor variable area, based on the good density.

A method for synchronizing virtual and real statuses of a digital twin system of an unmanned aerial vehicle (UAV) includes: performing parameter configuration for a virtual object system and a physical object system of the UAV; performing time synchronization between the virtual object system and the physical object system; detecting an event trigger type, wherein the event trigger type is a training event or a monitoring event; and triggering a corresponding synchronization controller based on the detected event trigger type, such that the synchronization controller performs result synchronization and process synchronization for the virtual object system and the physical object system based on the event trigger type, where a synchronization controller corresponding to the training event is a controller for synchronizing a physical object to a virtual object, and a synchronization controller corresponding to the monitoring event is a controller for synchronizing the virtual object to the physical object.

A method for synchronizing virtual and real statuses of a digital twin system of an unmanned aerial vehicle (UAV) includes: performing parameter configuration for a virtual object system and a physical object system of the UAV; performing time synchronization between the virtual object system and the physical object system; detecting an event trigger type, wherein the event trigger type is a training event or a monitoring event; and triggering a corresponding synchronization controller based on the detected event trigger type, such that the synchronization controller performs result synchronization and process synchronization for the virtual object system and the physical object system based on the event trigger type, where a synchronization controller corresponding to the training event is a controller for synchronizing a physical object to a virtual object, and a synchronization controller corresponding to the monitoring event is a controller for synchronizing the virtual object to the physical object.

A dynamic learning method for a robot includes a training and learning mode. The training and learning mode includes the following steps: dynamically annotating a belonging and use relationship between an object and a person in a three-dimensional environment to generate an annotation library; acquiring a rule library, and establishing a new rule and a new annotation by means of an interactive demonstration behavior based on the rule library and the annotation library; and updating the new rule to the rule library and updating the new annotation to the annotation library when it is determined that the established new rule is not in conflict with rules in the rule library and the new annotation is not in conflict with annotations in the annotation library.

A dynamic learning method for a robot includes a training and learning mode. The training and learning mode includes the following steps: dynamically annotating a belonging and use relationship between an object and a person in a three-dimensional environment to generate an annotation library; acquiring a rule library, and establishing a new rule and a new annotation by means of an interactive demonstration behavior based on the rule library and the annotation library; and updating the new rule to the rule library and updating the new annotation to the annotation library when it is determined that the established new rule is not in conflict with rules in the rule library and the new annotation is not in conflict with annotations in the annotation library.

Systems and methods provide automatic assignment of control of a plurality of hydraulic circuits of an associated work vehicle to a plurality of operation systems of an implement. A hydraulic circuit assignment control unit includes a processor, a memory device, logic stored in the memory device, and a communication circuit operatively coupled with the processor. The processor executes the logic to associate an activation of a first hydraulic circuit of the plurality of hydraulic circuits of the associated work vehicle with a physical exercise of an operation system of the plurality of operation systems of the associated implement, and generates pairing assignment data representative of the association of the activated first hydraulic circuit with the physical exercise of the operation system of the implement. The logic generates directionality confirmation and calibration data that is communicated to the plurality of operation systems with the pairing assignment data.

Systems and methods provide automatic assignment of control of a plurality of hydraulic circuits of an associated work vehicle to a plurality of operation systems of an implement. A hydraulic circuit assignment control unit includes a processor, a memory device, logic stored in the memory device, and a communication circuit operatively coupled with the processor. The processor executes the logic to associate an activation of a first hydraulic circuit of the plurality of hydraulic circuits of the associated work vehicle with a physical exercise of an operation system of the plurality of operation systems of the associated implement, and generates pairing assignment data representative of the association of the activated first hydraulic circuit with the physical exercise of the operation system of the implement. The logic generates directionality confirmation and calibration data that is communicated to the plurality of operation systems with the pairing assignment data.

A feedforward control method comprising steps of: acquiring kinematic parameters of each joint of a robot based on inverse kinematics according to a pre-planned robot motion trajectory, and setting a center of a body of the robot as a floating base; determining a six-dimensional acceleration of a center of mass of each joint of the robot in a base coordinate system using a forward kinematics algorithm, based on the kinematic parameters of each joint of the robot, and converting the six-dimensional acceleration of the center of mass of each joint of the robot in the base coordinate system to a six-dimensional acceleration in a world coordinate system; and calculating a torque required by a motor of each joint of the robot using an inverse dynamic algorithm, and controlling the motors of corresponding joints of the robot.

A feedforward control method comprising steps of: acquiring kinematic parameters of each joint of a robot based on inverse kinematics according to a pre-planned robot motion trajectory, and setting a center of a body of the robot as a floating base; determining a six-dimensional acceleration of a center of mass of each joint of the robot in a base coordinate system using a forward kinematics algorithm, based on the kinematic parameters of each joint of the robot, and converting the six-dimensional acceleration of the center of mass of each joint of the robot in the base coordinate system to a six-dimensional acceleration in a world coordinate system; and calculating a torque required by a motor of each joint of the robot using an inverse dynamic algorithm, and controlling the motors of corresponding joints of the robot.