IP Library › Granted Patent US 12,442,158

Granted Patent B1

US 12,442,158 · App. 19/004,294 · Granted Oct 14, 2025

Automated training and use of predictive models for autonomous control of powered earth-moving vehicles

Inventors: Adam Sadilek (Monroe, WA); Ross Walker (Edinburgh, GB)

Assignee: AIM Intelligent Machines, Inc.

E02F9/2045 E02F9/2054 E02F9/26 G05B13/048 G07C5/008

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Quick Facts

Patent No.: US 12,442,158
App. No.: 19/004,294
Granted: Oct 14, 2025
Kind: B1

External Links

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Abstract

Systems and techniques are described for implementing autonomous control of powered earth-moving vehicles, including to automatically control movement of a vehicle's component parts on a job site to perform tasks. The techniques may include using an MPC-based Control System to perform a cycle of training and deployment of a predictive model specific to a particular earth-moving vehicle to control that vehicle's autonomous operations, and to further using resulting data in additional manners—such a cycle may include using a data gathering module on the vehicle to gather actual operational data of the vehicle during manual control of the vehicle on job site(s) by human operator(s) during performance of task(s), generating a 3D site map modeling the vehicle's surroundings, training a Model Predictive Control (MPC) model based on the actual operational data and 3D site map, and deploying the trained model to the vehicle for use in autonomous operations.

Claims (68)

1. A computer-implemented method comprising:

repeatedly, during operations of an earth-moving vehicle for performing one or more tasks on a site under control of at least one human operator,

transferring, by a computing device on the earth-moving vehicle and to one or more computing systems remote from the earth-moving vehicle, actual operational data gathered from the earth-moving vehicle during the performing of the one or more tasks, including data about inputs supplied by the at least one human operator to controls of the earth-moving vehicle, and including perception data from one or more sensors on the earth-moving vehicle indicating at least three-dimensional (3D) surfaces of an area of the site around the earth-moving vehicle, and including vehicle data from one or more additional sensors on the earth-moving vehicle regarding vehicle status and movements of components of the earth-moving vehicle;

updating, by the computing device on the earth-moving vehicle, and based on the perception data, a 3D map of the 3D surfaces of the area of the site around the earth-moving vehicle; and

training, by the one or more computing systems remote from the earth-moving vehicle and based on the transferred actual operational data, a model predictive control (MPC) vehicle behavior and environment dynamics model specific to the earth-moving vehicle, the MPC vehicle behavior and environment dynamics model encoding information about movements of the components of the earth-moving vehicle to implement the performing of the one or more tasks and about resulting changes to the 3D surfaces of the area of the site from the performing of the one or more tasks;

determining, after training the MPC vehicle behavior and environment dynamics model, to initiate autonomous operations on the earth-moving vehicle;

deploying, by at least one of the one or more computing systems remote from the earth-moving vehicle or the computing device on the earth-moving vehicle, a current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, including transferring the current copy from the one or more computing systems to the earth-moving vehicle; and

initiating, by the computing device on the earth-moving vehicle and using the deployed current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, the autonomous operations on the earth-moving vehicle.

2. The computer-implemented method of claim 1 wherein the initiating of the autonomous operations on the earth-moving vehicle further includes:

determining, by the deployed current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, further movements of the components of the earth-moving vehicle to perform at least one further task resulting in predicted changes to the 3D surfaces of the area of the site; and

initiating, by the computing device on the earth-moving vehicle, fully autonomous operations of the earth-moving vehicle to perform the further movements of the components of the earth-moving vehicle.

3. The computer-implemented method of claim 1 wherein the initiating of the autonomous operations on the earth-moving vehicle further includes:

determining, by the deployed current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, further movements of the components of the earth-moving vehicle for performing at least one further task resulting in predicted changes to the 3D surfaces of the area of the site;

monitoring, by the computing device on the earth-moving vehicle, further inputs supplied by at least one human operator to the controls of the earth-moving vehicle for performing the at least one further task; and

initiating, by the computing device on the earth-moving vehicle and as part of semi-autonomous operations of the earth-moving vehicle, one or more actions to implement at least one of the further movements based on at least one of the further inputs supplied by the at least one human operator.

4. The computer-implemented method of claim 1 wherein the transferring of the actual operational data further includes transferring the updated 3D map to the one or more computing systems remote from the earth-moving vehicle and further includes transferring data about inputs supplied by two or more human operators to the controls of the earth-moving vehicle during two or more task performance sessions, and wherein the training of the MPC vehicle behavior and environment dynamics model further includes using the transferred updated 3D map and the data about the inputs supplied by the two or more human operators to the controls of the earth-moving vehicle during the two or more task performance sessions.

5. The computer-implemented method of claim 1 further comprising:

generating, by at least one of the computing device or the one or more computing systems, analytics information about performance of the earth-moving vehicle for a plurality of defined metrics over one or more periods of time; and

providing the analytics information.

6. The computer-implemented method of claim 5 further comprising:

obtaining, by the one or more computing systems and for each of a plurality of additional earth-moving vehicles separate from the earth-moving vehicle, additional actual operational data gathered from that additional earth-moving vehicle during performing of at least one task by that additional earth-moving vehicle under control of one or more human operators, wherein the plurality of additional earth-moving vehicles are of a vehicle type that is same as the earth-moving vehicle and are operated by a same entity operating the earth-moving vehicle;

generating, by the one or more computing systems and for each of the plurality of additional earth-moving vehicles, additional analytics information about performance of that additional earth-moving vehicle for the plurality of defined metrics over the one or more periods of time;

determining, by the one or more computing systems, aggregated analytics information for the plurality of defined metrics by combining the generated analytics information for the earth-moving vehicle and the generated additional analytics information for each of the plurality of additional earth-moving vehicles; and

providing the determined aggregated analytics information.

7. The computer-implemented method of claim 6 further comprising analyzing, by the one or more computing systems, the determined aggregated analytics information to determine one or more suggested improvements for manual performance of one or more tasks by earth-moving vehicles of the vehicle type, and providing the determined one or more suggested improvements for the manual performance of the one or more tasks.

8. The computer-implemented method of claim 1 wherein the earth-moving vehicle is one of an excavator or a bulldozer, wherein the one or more sensors on the earth-moving vehicle include at least one of one or more LiDAR sensors or one or more image sensors, wherein the one or more additional sensors on the earth-moving vehicle include one or more GPS sensors on a chassis of the earth-moving vehicle and one or more inclinometer sensors on one or more of the components of the earth-moving vehicle and one or more pressure sensors on at least one of the components of the earth-moving vehicle, and wherein the method further comprises, after the initiating of the autonomous operations and based on further input received from a human operator, changing a type of the autonomous operations for further activities performed on the earth-moving vehicle.

9. The computer-implemented method of claim 1 wherein the transferring of the actual operational data to the one or more computing systems remote from the earth-moving vehicle is performed by an operational data gatherer module executing on the computing device on the earth-moving vehicle, wherein the training of the MPC vehicle behavior and environment dynamics model is performed by a model training module executing on the one or more computing systems remote from the earth-moving vehicle, and wherein the deploying of the current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle is performed by a deployment module executing on one of the computing device on the earth-moving vehicle or on the one or more computing systems remote from the earth-moving vehicle.

10. A system, comprising:

one or more first sensors mounted on an earth-moving vehicle on a site to obtain environment data about an area of the site around the earth-moving vehicle, including at least one of one or more LiDAR sensors, or one or more image capture devices;

a plurality of second sensors mounted on the earth-moving vehicle to obtain vehicle data about the earth-moving vehicle, including one or more GPS antennas on a cabin of the earth-moving vehicle, and one or more inclinometers mounted on movable components of the earth-moving vehicle; and

a computing device on the earth-moving vehicle having one or more hardware processors and one or more memories, the one or more memories having software instructions of one or more software modules that, when executed by the one or more hardware processors, cause the computing device to perform automated operations including at least:

repeatedly, during operations of the earth-moving vehicle for performing one or more tasks on a site under control of at least one human operator,

updating, based on perception data from the one or more first sensors indicating at least surfaces of the area of the site around the earth-moving vehicle, a site map of the surfaces of the area of the site around the earth-moving vehicle; and

training, using actual operational data gathered from the earth-moving vehicle during the performing of the one or more tasks that includes data about inputs supplied by the at least one human operator to controls of the earth-moving vehicle and includes the perception data and includes vehicle data from the plurality of second sensors regarding vehicle status and movements of components of the earth-moving vehicle, a model predictive control (MPC) vehicle behavior and environment dynamics model specific to the earth-moving vehicle, the MPC vehicle behavior and environment dynamics model encoding information about movements of the components of the earth-moving vehicle to implement the performing of the one or more tasks and about resulting changes to the surfaces of the area of the site from the performing of the one or more tasks;

determining, after training the MPC vehicle behavior and environment dynamics model, to initiate autonomous operations on the earth-moving vehicle; and

initiating, using a deployed current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, the autonomous operations on the earth-moving vehicle.

11. The system of claim 10 further comprising one or more computing systems remote from the earth-moving vehicle, the one or more computing systems having one or more additional hardware processors and one or more additional memories, the one or more additional memories having additional software instructions of one or more additional software modules that, when executed by the one or more additional hardware processors, cause the one or more computing systems to perform additional automated operations including at least:

repeatedly receiving actual operational data that is transferred from the computing device on the earth-moving vehicle;

performing the repeated training of the MPC vehicle behavior and environment dynamics model on the one or more computing systems based on the transferred actual operational data; and

transferring the current copy of the trained MPC vehicle behavior and environment dynamics model from the one or more computing systems to the earth-moving vehicle, to cause deploying of the current copy of the trained MPC vehicle behavior and environment dynamics model to the earth-moving vehicle.

12. The system of claim 11 wherein the additional automated operations further include:

generating analytics information about performance of the earth-moving vehicle for a plurality of defined metrics over one or more periods of time; and

providing the analytics information.

13. The system of claim 12 wherein the additional automated operations further include:

obtaining, for each of a plurality of additional earth-moving vehicles separate from the earth-moving vehicle, additional actual operational data gathered from that additional earth-moving vehicle during performing of at least one task by that additional earth-moving vehicle under control of one or more human operators, wherein the plurality of additional earth-moving vehicles are of a vehicle type that is same as the earth-moving vehicle;

generating, for each of the plurality of additional earth-moving vehicles, additional analytics information about performance of that additional earth-moving vehicle for the plurality of defined metrics over the one or more periods of time;

determining aggregated analytics information for the plurality of defined metrics by combining the generated analytics information for the earth-moving vehicle and the generated additional analytics information for each of the plurality of additional earth-moving vehicles;

analyzing the determined aggregated analytics information to determine or more suggested improvements for manual performance of one or more tasks by earth-moving vehicles of the vehicle type; and

providing the determined one or more suggested improvements for the manual performance of the one or more tasks.

14. The system of claim 11 wherein transferring of the actual operational data to the one or more computing systems remote from the earth-moving vehicle is performed by an operational data gatherer module executing on the computing device on the earth-moving vehicle, wherein the training of the MPC vehicle behavior and environment dynamics model is performed by a model training module executing on the one or more computing systems remote from the earth-moving vehicle, and wherein deploying of the current copy of the trained MPC vehicle behavior and environment dynamics model to the earth-moving vehicle is performed by a deployment module executing on at least one of the computing device on the earth-moving vehicle or the one or more computing systems remote from the earth-moving vehicle.

15. The system of claim 11 wherein transferring of the actual operational data from the computing device on the earth-moving vehicle to the one or more computing systems remote from the earth-moving vehicle further includes transferring the updated site map to the one or more computing systems remote from the earth-moving vehicle and further includes transferring data about inputs supplied by two or more human operators to the controls of the earth-moving vehicle during two or more task performance sessions, and wherein training of the MPC vehicle behavior and environment dynamics model further includes using the transferred updated site map and the data about the inputs supplied by the two or more human operators to the controls of the earth-moving vehicle during the two or more task performance sessions.

16. The system of claim 10 wherein the initiating of the autonomous operations on the earth-moving vehicle further includes:

initiating fully autonomous operations of the earth-moving vehicle to perform the further movements of the components of the earth-moving vehicle.

17. The system of claim 10 wherein the initiating of the autonomous operations on the earth-moving vehicle further includes:

determining, by the deployed current copy of the trained MPC vehicle behavior and environment dynamics model on the earth-moving vehicle, further movements of the components of the earth-moving vehicle for performing at least one further task resulting in predicted changes to the surfaces of the area of the site;

monitoring further inputs supplied by the at least one human operator to the controls of the earth-moving vehicle for performing the at least one further task; and

initiating, as part of semi-autonomous operations of the earth-moving vehicle, one or more actions to implement at least one of the further movements based on at least one of the further inputs supplied by the at least one human operator.

18. The system of claim 10 wherein the earth-moving vehicle is one of an excavator or a bulldozer, and wherein the automated operations further include, after the initiating of the autonomous operations and based on further input received from a human operator, changing a type of the autonomous operations for further activities performed on the earth-moving vehicle.

19. A computer-implemented method comprising:

transferring, by a computing device on an earth-moving vehicle on a site and to one or more computing systems remote from the earth-moving vehicle, actual operational data gathered from the earth-moving vehicle during performing of one or more tasks under control of at least one human operator, including data about inputs supplied by the at least one human operator to controls of the earth-moving vehicle, and including perception data from one or more sensors on the earth-moving vehicle indicating at least surfaces of an area of the site around the earth-moving vehicle, and including vehicle data from one or more additional sensors on the earth-moving vehicle regarding vehicle status and movements of components of the earth-moving vehicle;

updating, by the computing device on the earth-moving vehicle, and based on the perception data, a map of the surfaces of the area of the site around the earth-moving vehicle;

training, by the one or more computing systems remote from the earth-moving vehicle and based on the transferred actual operational data, a vehicle behavior and environment dynamics model that is specific to the earth-moving vehicle and that represents information about movements of the components of the earth-moving vehicle to implement the performing of the one or more tasks and about resulting changes to the surfaces of the area of the site from the performing of the one or more tasks;

deploying, by at least one of the one or more computing systems remote from the earth-moving vehicle or the computing device on the earth-moving vehicle, a current copy of the trained vehicle behavior and environment dynamics model on the earth-moving vehicle, including transferring the current copy from the one or more computing systems to the earth-moving vehicle; and

initiating, by the computing device on the earth-moving vehicle and using the deployed current copy of the trained vehicle behavior and environment dynamics model on the earth-moving vehicle, autonomous operations on the earth-moving vehicle.

20. The computer-implemented method of claim 19 wherein the initiating of the autonomous operations on the earth-moving vehicle further includes:

determining, by the deployed current copy of the trained vehicle behavior and environment dynamics model on the earth-moving vehicle, further movements of the components of the earth-moving vehicle to perform at least one further task resulting in predicted changes to the surfaces of the area of the site; and

performing, by the computing device on the earth-moving vehicle, fully autonomous operations of the earth-moving vehicle to perform the further movements of the components of the earth-moving vehicle, or semi-autonomous operations of the earth-moving vehicle to implement at least one of the further movements based on a further input supplied by at least one human operator to the controls of the earth-moving vehicle for performing the at least one further task.

Assignments (1)

ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 7, 2025

From: SADILEK, ADAM; WALKER, ROSS

To: AIM INTELLIGENT MACHINES, INC.

Reel/Frame 069774/0899 →

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