Caterpillar Inc.

Other

Frank Arthur Willis

Paul Russell Friend

Qi Chen

Drew Alan Fehr

Troy Kenneth Becicka

Andrew Whitten

Hong Chang

Nicholas Robert Vogel

Timothy A Evans

Salman Chikni

A method and a system of determining a position of a mobile machine are disclosed. According to certain embodiments, the system may include a first sensor configured to generate a first signal indicative of a parameter of the mobile machine. The system may also include a second sensor configured to generate a second signal indicative of a pose of the mobile machine. The system may further include a controller in communication with the first and second sensors. The controller may be configured to generate one or more estimated poses of the mobile machine based on the first signal. The controller may further be configured to update each estimated pose with a fraction of a correction. The correction may be determined, based on the second signal, in a measurement update stage of a Kalman filter.

Positioning system having smoothed kalman filter update

A system for monitoring positioning of a machine is disclosed. The system includes an IMU located at a first location on the machine and configured to generate positioning data associated with the first location. The system includes a machine controller operatively associated with the machine. The machine controller is configured to determine predicted positioning data for a second location on the machine based on positioning data associated with the first location. The machine controller is further configured to generate a virtual IMU at the second location based on the predicted positioning data for the second location, wherein the virtual IMU generates virtual positioning data for the second location. The system further includes an application controller operatively associated with the machine controller and configured to use the virtual positioning data as input data for one or more machine-associated applications.

Systems and methods for monitoring positioning of a machine by utilizing a virtual IMU

A method of determining a heading of a machine having an implement is provided. The method includes determining a first heading data of the machine using an inertial sensor. The method includes determining a second heading data of the machine using a magnetometer. The method includes determining a position of the implement in a stationary state. The method also includes calculating a corrected second heading data based on a predefined relation between the position of the implement in the stationary state and the second heading data. The method further includes determining the heading of the machine based on the first heading data and the corrected second heading data.

Navigation system and method for machine

A system having a primary inertial measurement unit and a secondary inertial measurement unit configured to generate a primary position signal and a secondary position signal respectively is provided. The system also includes an error detection module communicably coupled to the primary inertial measurement unit and the secondary inertial measurement unit. The error detection module is configured to receive the primary position signal and the secondary position signal and detect if an out-range error is present in at least one of the primary position signal and the secondary position signal. The error detection module is also configured to detect if an in-range error is present in at least one of the primary position signal and the secondary position signal and determine an action to be performed based on the presence of at least one of the out-range error and the in-range error.

System and method for estimating position of machine

A method and system for determining an alignment error between sensors mounted to a machine is disclosed. The method may include calculating a first orientation value based on a signal received from a first sensor. The method may further include calculating a second orientation value based on a signal received from a second sensor. The method may further include calculating an alignment error between the first sensor and the second sensor based on a difference between the first orientation value and the second orientation value.

Machine positioning system having alignment error detection

A system and method for estimating position of a machine is disclosed. The method may include receiving, from a perception sensor, scene data describing an environment in a vicinity of the machine and estimating a first position of the machine based on the scene data. The method may include determining whether a first signal indicative of a location of the machine is received by the machine and estimating a second position of the machine when it is determined that the first signal is received. The method may include comparing the second position with the first position and estimating a third position of the machine using at least one of the first position and the second position.

Machine positioning system utilizing position error checking

An inclination detection system is disclosed. The inclination detection system may have an inclination angle predictor configured to calculate an a priori estimated inclination angle of the machine based on a previously estimated inclination angle, and a measurement variance calculator configured to calculate a measurement variance of the a priori estimated inclination angle based on a non-gravitational acceleration of the machine. The inclination detection system may also have an inclination angle sensor configured to measure a measured inclination angle of the machine, and an inclination angle updater configured to determine an a posteriori estimated inclination angle of the machine based on the a priori estimated inclination angle, the measurement variance of the a priori estimated inclination angle, and the measured inclination angle.

Inclination detection systems and methods

A machine navigation system and method for estimating velocity of a machine is disclosed. The method may include receiving, from an odometer, a first signal indicative of a distance traveled by the machine and calculating a scale factor to compensate for an error associated with the first signal. The method may further include determining whether a second signal indicative of a location of the machine is received by the machine and selectively adjusting the scale factor using machine parameters to generate an adjusted scale factor, where selectively adjusting may be performed based on whether the second signal is received by the machine. The method may further include estimating the velocity of the machine based on the first signal and the adjusted scale factor.

Machine navigation system utilizing scale factor adjustment

An operational parameter determination system is disclosed. The operational parameter determination system may include an operational parameter predictor configured to calculate an a priori estimated operational parameter of the machine based on a previously estimated operational parameter. The operational parameter determination system may also include a gear shifting compensator configured to determine whether a gear shifting is in progress, and when the gear shifting is in progress, to output the a priori estimated operational parameter as a determined operational parameter. The operational parameter determination system may further include an operational parameter updater configured to, when the gear shifting is not in progress, receive a measured operational parameter of the machine, determine an a posteriori estimated operational parameter of the machine based on the a priori estimated operational parameter and the measured operational parameter, and output the a posteriori estimated operational parameter as the determined operational parameter.

Operational parameter determination systems and methods with gear shifting compensation

Data acquisition times from a component under test in resonant ultrasound spectroscopy are decreased. A proximity of each data acquisition point to a resonant response of the component is monitored. A dwell time between successive data acquisition points is then adjusted as a function of the proximity to a resonant response. In one embodiment, each component response is compared to a preselected threshold value and the dwell time between adjacent data points is increased when the response exceeds the threshold value, indicating the response is nearing a resonance. The dwell time is decreased between resonant responses to decrease the data acquisition time.

Growing community of inventors

Canton, IL, United States of America

Frank Arthur Willis