Vision-based detection and control of machinery

1 . A system for altering an operational condition of a material-handling vehicle (MHV) comprising:

a computer system having a processor configured to analyze visual data using a machine learning (ML) engine;

a vision system comprising at least one camera that is configured to mount to the MHV, to generate visual data by imaging an observed area proximate the MHV, and to transmit the visual data to the computer system for analysis; and

a controller operatively connected to the MHV and configured to receive an operational set point for the MHV and to execute operational commands generated by the processor, where such commands modify an operational condition of the MHV when executed by the controller,

wherein the computer system is configured to:

receive the visual data transmitted from the vision system;

analyze the visual data using the ML engine to determine if a current operational condition of the MHV is within a tolerance band of the operational set point; and

when the current operational condition of the MHV is outside of the tolerance band of the operational set point, to generate operational commands for modifying the operational condition that are calculated to bring the current operational condition of the MHV within the tolerance band of the operational set point.

2 . The system of claim 1 wherein the vision system comprises at least one of a standard camera, stereoscopic camera, infrared camera, LiDAR, or time of flight sensor.

3 . The system of claim 1 wherein the MHV is configured to move a material from a first location to a second location and to discharge the material at a discharge area located at the second location.

4 . The system of claim 3 wherein the observed area comprises the second location and the discharge area, and

wherein the visual data from the vision system comprises a at least one of: a shape of a discharge pile, dimensional constraints of a discharge receptacle, proximity to the discharge area, a discharge rate, or a fill rate of the discharge receptacle.

5 . The system of claim 3 wherein the current operational condition includes a discharge speed, or a position of at least a portion of the MHV with respect to a reference, and wherein the operational commands modify the discharge speed or the position of the at least portion of the MHV with respect to the reference.

6 . The system of claim 3 wherein the MHV comprises a milling machine having a discharge conveyor having a receiving end and a discharge end, and

wherein the discharge area comprises a bed of a dump truck.

7 . The system of claim 3 wherein the MHV comprises a material transfer vehicle (MTV) having a discharge conveyor having a receiving end and a discharge end.

8 . The system of claim 7 wherein the discharge area comprises a receiving hopper disposed on a paving machine.

9 . The system of claim 3 wherein the MHV comprises a stacking conveyor having a receiving end and a discharge end, and

wherein the discharge area comprises a gravel pile.

10 . The system of claim 9 further comprising a second MHV configured to move the material from a third location to a fourth location and to discharge the material at a discharge area located at the fourth location, the second MHV comprising a second stacking conveyor; and

a second system for altering an operational condition of the second MHV, the system comprising:

a second computer system having a second processor configured to analyze visual data using a machine learning (ML) engine;

a second vision system comprising at least one camera that is configured to mount to the second MHV, to generate visual data by imaging a second observed area proximate the MHV, and to transmit the visual data to the second computer system for analysis; and

a second controller operatively connected to the second MHV and configured to receive an operational set point for the second MHV and to execute operational commands generated by the second processor, where such commands modify an operational condition of the second MHV when executed by the second controller,

wherein the second computer system is configured to:

receive the visual data transmitted from the second vision system;

analyze the visual data using the ML engine to determine if a current operational condition of the second MHV is within a tolerance band of the operational set point;

where the current operational condition of the second MHV is outside of the tolerance band of the operational set point, to generate operational commands for modifying the operational condition that are calculated to bring the current operational condition of the second MHV within the tolerance band of the operational set point, and

wherein the discharge area at the fourth location corresponds to the receiving end of the first MHV.

11 . A method for altering an operational condition of a material-handling vehicle (MHV) including the steps of:

providing the MHV at a first location;

providing a system for altering an operational condition of the MHV, the system comprising:

a computer system having a processor configured to analyze visual data using a machine learning (ML) engine;

a vision system comprising at least one camera mounted to the MHV and configured to generate visual data by imaging an observed area proximate the MHV and to transmit the visual data to the computer system for analysis; and

a controller configured to receive an operational set point for the MHV and to execute operational commands generated by the processor, where such commands modify the operational condition of the MHV when executed by the controller,

wherein the computer system is configured to:

receive the visual data transmitted from the vision system;

analyze the visual data using the ML engine to determine if a current operational condition of the MHV is within a tolerance band of the operational set point;

where the current operational condition of the MHV is outside of the tolerance band of the operational set point, to generate operational commands for modifying the operational condition that are calculated to bring the current operational condition of the MHV within the tolerance band of the operational set point,

placing a material on the MHV;

inputting the operational set point to the controller;

moving the material, using the MHV, to a second location;

using the vision system, imaging the observed area and generating visual data related to the observed area;

transmitting the visual data to the computer system;

analyzing said visual data with ML engine of the computer system;

determining if the current operational condition of the MHV is outside of the tolerance band of the operational set point;

if the current operational condition of the MHV is outside of the tolerance band of the operational set point, generating operational commands for bringing the current operational condition within the tolerance band of the operational set point;

transmitting the operational commands to the controller;

using the controller, modifying the operational condition of the MHV.

12 . The method of claim 11 wherein the MHV is configured to move a material from a first location to a second location and to discharge the material at a discharge area located at the second location.

13 . The method of claim 12 wherein the observed area comprises the second location and the discharge area, and

wherein the visual data from the vision system comprises a shape of a discharge pile, dimensional constraints of a discharge receptacle, or proximity to the discharge area.

14 . The method of claim 12 wherein the current operational condition includes a discharge speed, or a position of the MHV with respect to the discharge area, and

wherein the operational commands modify the discharge speed or the position of the MHV with respect to the discharge area.

15 . The method of claim 12 wherein the vision system is at least one of a standard camera, stereoscopic camera, infrared camera, LiDAR, or time of flight sensor.

16 . The method of claim 12 wherein the MHV comprises a material transfer vehicle (MTV) having a discharge conveyor having a receiving end and a discharge end, and wherein the discharge area comprises a receiving hopper disposed on a paving machine.

17 . The method of claim 12 wherein the MHV comprises a milling machine having a discharge conveyor having a receiving end and a discharge end, and wherein the discharge area comprises a bed of a dump truck.

18 . The method of claim 12 wherein the MHV comprises a stacking conveyor having a receiving end and a discharge end, and

wherein the discharge area comprises a gravel pile.

19 . The method of claim 18 further comprising the steps of:

providing a second MHV configured to move the material from a third location to a fourth location and to discharge the material at a discharge area located at the fourth location, the second MHV comprising a second stacking conveyor; and

providing a second system for altering an operational condition of the second MHV, the system comprising:

a second computer system having a second processor configured to analyze visual data using a machine learning (ML) engine;

a second vision system comprising at least one camera that is configured to mount to the second MHV, to generate visual data by imaging a second observed area proximate the MHV, and to transmit the visual data to the second computer system for analysis; and

a second controller operatively connected to the second MHV and configured to receive an operational set point for the second MHV and to execute operational commands generated by the second processor, where such commands modify an operational condition of the second MHV when executed by the second controller,

wherein the second computer system is configured to:

receive the visual data transmitted from the second vision system;

analyze the visual data using the ML engine to determine if a current operational condition of the second MHV is within a tolerance band of the operational set point;

where the current operational condition of the second MHV is outside of the tolerance band of the operational set point, to generate operational commands for modifying the operational condition that are calculated to bring the current operational condition of the second MHV within the tolerance band of the operational set point, and

wherein the discharge area at the fourth location corresponds to the receiving end of the first MHV,

placing the material on the second MHV;

inputting the operational set point to the second controller;

moving the material, using the second MHV, to the fourth location;

using the second vision system, imaging the discharge area and generating visual data related to the discharge area;

transmitting the visual data to the second computer system;

analyzing said visual data with ML engine of the second computer system;

determining if the current operational condition of the second MHV is outside of the tolerance band of the operational set point;

if the current operational condition of the second MHV is outside of the tolerance band of the operational set point, generating operational commands for bringing the current operational condition within the tolerance band of the operational set point;

transmitting the operational commands to the second controller; and

using the controller, modifying the operational condition of the second MHV.

20 . A system for positioning and operating a conveyor, the system comprising:

the conveyor having a receiving end and a discharge end and being configured to convey an aggregate from the receiving end to the discharge end;

a vision sensor configured to sense a discharge area, generate data related to the discharge area, and transmit said data;

a processor configured to receive and analyze the data from the vision sensor and generate commands to modify an operational condition of the conveyor; and

a controller operatively connected to the conveyor for receiving and executing the commands generated by the processor,

wherein, based on the commands, the controller adjusts a physical location of the discharge end and a discharge speed of the conveyor;

wherein the vision sensor is at least one of a standard camera, a stereoscopic camera, an infrared camera, or a time-of-flight sensors;

wherein the vision system is mounted to the discharge end of the conveyor;

wherein the processor utilizes a neural network to analyze said data;

wherein the discharge area is a hopper configured to receive aggregate; and

wherein the physical location of the discharge end is changeable in three directions.