REALTIME PAYLOAD MAPPING FOR LOADER/HAULER SYSTEM OPTIMIZATION

FIELD OF THE DISCLOSURE

The present disclosure relates generally to hauling and loading machines and, more particularly, relates to a system for optimizing the loading of a hauling machine.

BACKGROUND OF THE DISCLOSURE

Work machines, such as hauling trucks, loaders, shovels, excavators, articulated trucks, off-road machines, on-road machines, dozers, and the like may be used in mining, construction, agriculture, petroleum, and other such applications. During operation, one or more work machines may work together to perform a desired task. In one non-limiting example, a hauling machine and a loading machine may be paired together at a jobsite. The loading machine may be tasked with scooping up material in a loading bucket and filling a hauling body of the hauling machine. In some cases the loading machine may be configured to scoop and load a variety of work material into the hauling machine such as large rocks or boulder, small rocks, gravel, dirt, and the like.

Typically, an operator of the loading machine may be tasked with deciding which work material to scoop up with the loading bucket and dump into the hauling machine. Furthermore, it may be left to the operator of the loading machine to make the decision where to specifically dump the work material within the hauling body of the hauling machine. However, each load of work material may exhibit a variation in total weight and volume due to the loads having a different composition of large rocks, small rocks, dirt, gravel, and the like. As a result, it may be difficult for the operator to properly balance each load when placing it into the hauling machine. For example, the operator may not be able to properly view the previously placed loads. Therefore the operator may be unable to pick out the best place to dump subsequent loads of work material into the hauling body. Additionally, some operators may not have sufficient knowledge or training in the proper loading techniques for the variety of work machines present at the jobsite. As a result, it may be desired to configure a system to analyze and monitor the hauling and loading machine such that the system may be able to determine an optimized position for placing the work material into the hauling machine.

A system and method for automating a task of a construction machine is disclosed in U.S. Patent Application Publication No. 2015/0376869 entitled, “Method and Apparatus for Machine Synchronization,” (the '869 publication). The synchronization system disclosed therein is installed on construction machines and configured to facilitate the exchange of information between two or more machines over a communications network. The synchronization system of the '869 publication further includes sensors located on the machines which provide on-board measurements such as swing data, tilt and positioning. Additionally, the machines may be configured to automate the task of loading a dump truck. On board measurements of the excavator and dump truck are processes and applied against a model of operational practices to generate the automated control messages. The release location where the excavator dumps the load is determined based on the load-imbalance data from sensors on the dump truck. One or more load sensors may be placed throughout the bed of the dump truck or may be placed on a bucket of the excavator.

However, the '869 publication does not visually scan the dump truck bed to produce an image map of the dump truck bed which is analyzed to determine an optimized location for the excavator to place the load on the dump truck.

SUMMARY OF THE DISCLOSURE

In accordance with one embodiment, a payload optimization system for loading a set of work machines is disclosed. The payload optimization system may include one or more visual sensors operably coupled to a hauling machine, the one or more visual sensors configured to scan a payload body of the hauling machine and produce a payload body visual data set. The payload optimization system may further comprise a loading machine including a payload bucket configured to load a payload into the payload body of the hauling machine. Moreover, a loading system controller may be communicably coupled to each of the hauling machine and the loading machine. The loading system controller may be configured to identify the hauling machine and the loading machine using a set of machine identifiers received from the hauling machine and the loading machine. Additionally, the loading system controller may receive the payload body visual data set from the one or more visual sensors and generate a payload body map based on the payload body visual data set. Furthermore, the loading system controller may program a loading sequence of the payload body based on the payload body map and transmit the loading sequence to the loading machine. The loading system controller may display the loading sequence on a loading machine display device and the loading sequence may be configured to guide a loading cycle between the hauling machine and the loading machine.

In accordance with another embodiment, a method of optimizing a payload position within a work machine is disclosed. The method may include identifying a hauling machine and a loading machine using one or more visual sensors coupled to a frame of the hauling machine. The method may further include receiving a payload capacity of the hauling machine from a machine specification data base on an identification of the hauling machine. Scanning a payload body of the hauling machine with the one or more visual sensors to produce a payload body visual data set. The method may further include generating a payload body map based on the payload body data set and programming a loading sequence of the payload body based on the payload body map and the loading capacity of the loading machine. Moreover, the method may include transmitting the loading sequence to the loading machine to guide a loading cycle of the hauling machine.

In accordance with yet another embodiment, a controller for optimizing the operation of a work machine is disclosed. The controller may include a machine specification module including a payload capacity for a hauling machine and a loading capacity for a loading machine. The controller may further include a vision data module configured to receive a visual data set collected from one or more visual sensors operably coupled to the hauling machine and the one or more visual sensors may be configured to scan a payload body of the hauling machine and produce a payload body data set. Moreover, a payload mapping module may be configured to receive the payload body data set and generate a payload body map. The controller may further include a loading sequence module which is configured to program a loading sequence of the payload body of the hauling machine based on the payload body map and the loading capacity. Additionally, the controller may include a communication module configured to transmit the loading sequence to the loading machine to guide a loading cycle of the hauling machine.

These and other aspects and features of the present disclosure will be more readily understood upon reading the following detailed description in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a perspective view of a set of work machines at a jobsite, in accordance with an embodiment of the present disclosure;

FIG. 2 is a schematic view of an exemplary jobsite including the set of work machines of FIG. 1, in accordance with an embodiment of the present disclosure;

FIG. 2a is a schematic side view of one machine of the set of work machines of FIG. 1, in accordance with an embodiment of the present disclosure;

FIG. 2b is a schematic top view of the set of work machines of FIG. 1 operating around the jobsite of FIG. 2, in accordance with an embodiment of the present disclosure;

FIG. 3 is a schematic view of an exemplary jobsite including the set of work machines of FIG. 1, in accordance with an embodiment of the present disclosure;

FIG. 3a is a schematic side view of one machine of the set of work machines of FIG. 1, in accordance with an embodiment of the present disclosure;

FIG. 3b is a schematic top view of the set of work machines of FIG. 1 operating around the jobsite of FIG. 3, in accordance with an embodiment of the present disclosure;

FIG. 4 is schematic diagram of a control system for optimizing the loading of the set of work machines of FIG. 1, in accordance with an embodiment of the disclosure; and

FIG. 5 is a flow chart of a method executed by the control system of FIG. 3 for optimizing the loading of the set of work machines of FIG. 1, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION

Referring now to the drawings and with specific reference to FIG. 1, a jobsite 20 with a set of work machines 22 is shown, in accordance with certain embodiments of the present disclosure. While one non-limiting example of the set of work machines 22 may include a hauling machine 24 and a loading machine 26, it will be understood that the set of work machines 22 may include other types of machines such as but not limited to, an on-road truck, an off-road truck, a motor grader, industrial mining equipment, a locomotive, and any other such machines. The hauling machine 24 may include a frame 28 configured to support a power source 30, and an operator compartment or operator cabin 32. In some embodiments, the power source 30 may be a power generating source such as but not limited to, a diesel combustion engine, a gasoline combustion engine, a generator, an electric motor, any other known power generating source or a combination thereof. Moreover, the operator compartment 32 may include a hauling machine control unit 34 and a set of operational controls such as but not limited to, a steering input device (not shown), throttle controls (not shown), machine implement controls (not shown), and other such operational controls. Alternatively, the hauling machine 24 may be configured as a fully autonomous vehicle and configured without the operator compartment 32. Moreover, in the fully autonomous configuration the hauling machine control unit 34, or other such controller, may be configured to control and operate the hauling machine 24 operational controls (i.e., electro-hydraulic controls, electric controls, or hydraulic controls). Additionally, the hauling machine 24 may include a payload body 36 or other such hauling container supported by the frame 28. In some embodiments, the payload body 36 may be configured to be filled with a work material 37 or payload such as dirt, stone, gravel, and the like. Moreover, the payload body 36 may be pivotally attached to the frame 28 and coupled to one or more dump actuators 38 such that the payload body 36 may be raised and/or lowered in order to empty the work material 37 from the payload body 36. The hauling machine 24 may further include a set of ground engaging elements 40 rotatably coupled to the frame 28 and driven by the power source 30 to propel the hauling machine 24 around the jobsite 20. Although the set of ground engaging elements 40 are shown as wheels, other types of engagement devices, such as continuous tracks and the like, may be used.

Similarly, the loading machine 26 may include a frame 42 configured to support a power source 44, and an operator compartment or operator cabin 46. In some embodiments, the power source 44 may be a power generating source such as but not limited to, a diesel combustion engine, a gasoline combustion engine, a generator, an electric motor, any other known power generating source or a combination thereof. Moreover, the operator compartment 46 may include a loading machine control unit 48 and a set of operational controls such as but not limited to, a steering input device (not shown), throttle controls (not shown), machine implement controls (not shown), and other such operational controls. Alternatively, the loading machine 26 may be configured as a fully autonomous vehicle and configured without the operator compartment 32. Moreover, in the fully autonomous configuration the loading machine control unit 48, or other such controller, may be configured to control and operate the loading machine 26 operational controls (i.e., electro-hydraulic controls, electric controls, or hydraulic controls). Additionally, the loading machine 26 may include a payload bucket 50 or other such loading apparatus. In some embodiments, the payload bucket 50 may be used to scoop or otherwise pick up the work material 37 or payload such as boulders, dirt, stone, gravel, and the like. Moreover, the payload bucket 50 may be coupled to one or more attachment arms 52 and movably attached to the frame 42. Furthermore, the one or more attachment arms 52 may include an actuator 54 configured to raise and/or lower the attachment arms 52 and the payload bucket 50. In one non-limiting example, an operator of the loading machine 26 may fill the payload bucket 50 with the work material 37 and load or otherwise dump it into the payload body 36 of the hauling machine 24. Moreover, the loading machine 26 may further include a set of ground engaging elements 56 rotatably coupled to the frame 42 and driven by the power source 44 to propel the loading machine 26 around the jobsite 20. Although the set of ground engaging elements 56 are shown as wheels, other types of engagement devices, such as continuous tracks and the like, may be used. It is to be understood that the set of work machines 22 is shown primarily for illustrative purposes to assist in disclosing features of various embodiments of the present disclosure, and that FIG. 1 may not depict all of the components of the set of work machines 22. Furthermore, a single set (i.e., one hauling machine 24 and one loading machine 26) of work machines 22 is shown for simplicity, and more than one set of work machines 22 may be in operation at the jobsite 20

Referring now to FIG. 2, with continued reference to FIG. 1, an exemplary jobsite 20 including the hauling machine 24 and loading machine 26 is shown. While a single hauling machine 24 and a single loading machine 26 is shown, it will be understood that multiple hauling, loading and other such machines and equipment may be operating around the jobsite 20. Furthermore, FIG. 2a illustrates a side view of the hauling machine 24 with an empty payload body 36, while FIG. 2b illustrates a top view of the hauling machine 24 and loading machine 26 operating around the jobsite 20. As further illustrated in FIG. 2b, during operation the loading machine 26 may be configured to scoop, or otherwise fill, the payload bucket 50 with the work material 37 (i.e., payload) and then position the load of work material 37 into the payload body 36 of the hauling machine 24. The loading machine 26 may deliver and position multiple loads of the work material 37 into the payload body 36. Once the payload body 36 is filled, the hauling machine 24 may transport the work material 37 to another location on the jobsite 20. Alternatively, the hauling machine 24 may transport the work material 37 to a location outside of the jobsite 20.

In one non-limiting example, the hauling machine 24 may include one or more visual sensors 58 such as but not limited to, a video camera, a RADAR scanning device, a LIDAR scanning device, 3D scanning device, or other such visual device. The one or more visual sensors 58 may be operably coupled to the payload body 36 or other such portion of the hauling machine 24 and configured to scan and monitor the payload body 36. In some embodiments, the one or more visual sensors 58 may be positioned to scan and monitor the payload body to produce a payload body visual data set. The payload body visual data set may provide visual images or other data of the interior of the payload body 36. For example, as illustrated in FIGS. 2a and 2b, the one or more visual sensors 58 may be mounted or otherwise arranged at an elevated position of the payload body and configured to scan and monitor a payload volume 60 of the payload body 36. Moreover, in some embodiments, the one or more visual sensors 58 may be adjustable such that an operator of the hauling machine 24 may control and adjust the one or more visual sensors 58 to scan and monitor different portions of the payload body 36. Additionally or alternatively, the one or more visual sensors 58 may be controllably configured to scan the entire payload volume 60 of the payload body 36.

Prior to the start of a loading operation between the loading machine 26 and hauling machine 24, the one or more visual sensors 58 may be configured to scan and collect the payload body visual data set of the entire payload volume 60. The payload body visual data set may be analyzed by the hauling machine control unit 34 to confirm the payload body 36 is empty and ready to accept the work material 37 from the loading machine 26. If residual work material 37 is observed, the one or more visual sensors 58 may be configured to signal the operator of the hauling machine 24, the loading machine 26 or other interested personnel that the hauling machine 24 may not be ready to accept a load of work material 37. Alternatively, in the case where a set of fully autonomous work machines 22 are used at the jobsite 20, the one or more visual sensors 58 may be configured to signal an automated control system of the hauling machine 24 and/or loading machine 26 that the hauling machine 24 may not be ready to accept a load of work material 37. While FIGS. 2a and 2b show the one or more visual sensors 58 attached to the payload body 36 above the operator compartment 32, it will be understood that the one or more visual sensors 58 may be positioned in additional and/or alternative locations. In some embodiments the one or more visual sensors 58 may be mounted on both the hauling machine 24 and loading machine 26. Alternatively, the one or more visual sensors 58 may just be mounted on the loading machine 26 and configured to scan and monitor the work material 37 scooped up and contained within the payload bucket 50.

In addition to the one or more visual sensors 58, the hauling machine 24 and/or the loading machine 26 may have additional monitoring systems which have additional sensors, such as pressure sensors, positions sensors, strain sensors, orientation sensors, and other such sensors. In some embodiments, the hauling machine 24 and loading machine 26 may combine the data collected by the one or more visual sensors 58 with data collected by the additional sensors installed on the machine to confirm the payload body 36 is empty. For example, the hauling machine 24 may be equipped with sensors 62 such as but not limited to, pressure sensors, position sensors, strain sensors, vibration sensors, orientation sensors or other such sensors coupled to the suspension system 64 of the hauling machine 24. In some embodiments, the sensors 62 may be configured to provide a condition signal of the payload body 36 such as, full, partially full, empty, or other such condition. Moreover, the loading machine 26 may be configured with sensors 66, such as but not limited to, pressure sensors, position sensors, strain sensors, weight sensors, orientation sensors, vibration sensors, or other such sensors located on the payload bucket 50, the attachment arms 52 or other such location of the loading machine 26. The sensors 66 on the loading machine 26 may be configured to determine a weight and/or density of the work material 37 that is contained in the payload bucket 50.

The hauling machine 24 and the loading machine 26 may each respectively be configured with a hauling machine control unit 34 and loading machine control unit 48. Generally, the hauling machine control unit 34 and the loading machine control unit 48 may be configured to control and execute operational procedures of the machines. Moreover, the hauling machine control unit 34 may be configured with a hauling machine communication module 68 and loading machine control unit 48 may be configured with a loading machine communication module 70 such that a communication link 72 may be established between the hauling machine 24 and the loading machine 26. As a result, the hauling machine control unit 34 and the loading machine control unit 48 may communicate with each other, as well as, transmit data and other information to one another. Furthermore, the communication link 72 may utilize a wireless communication network 74 set up around the jobsite 20 which may enable direct communication and data transfer between the hauling machine communication module 68 and the loading machine communication module 70. The wireless communication network 74 may be configured as a data communication network such as, a Bluetooth network, a near-field communication network, a radio frequency communication network, a computer data network, a Wi-Fi data network, a cellular data network, a satellite data network, or other such data communication network. As a result, the hauling machine 24 and the loading machine 26 may be capable of transmitting or otherwise sharing voice data, visual data, machine data, and other such data between one another. For example, the payload body visual data set collected by the one or more visual sensors 58 may be transmitted from the hauling machine control unit 34 to the loading machine control unit 48 and the loading machine control unit 48 may utilize the payload body visual data set during the operation of the loading machine 26.

Additionally, a back office operations center 76 may be located somewhere around the jobsite 20, and the back office operations center 76 may include a loading system controller 78 that is programmed or otherwise configured to monitor, command and control the movement and activity of the hauling machine 24, the loading machine 26 and other such equipment located around the jobsite 20. In some embodiments, the loading system controller 78 may be communicably coupled with the hauling machine communication module 68 and the loading machine communication module 70 through the wireless communications network 74 described above (i.e., Bluetooth network, near-field communication network, radio frequency communication network, computer data network, Wi-Fi data network, cellular data network, satellite data network, or other such data communication network). As a result, the loading system controller 78, the hauling machine control unit 34, and the loading machine control unit 48 may all be communicably coupled and configured to transmit and receive data between one another.

The loading system controller 78 may be configured to analyze the workload around the jobsite 20 and implement an operation plan which may minimize the loading cycle between the hauling machine 24 and the loading machine 26. Such optimization not only may improve efficiency around the jobsite 20 but may produce other benefits as well such as but not limited to, reducing fuel consumption, increasing operational lifespan of the hauling machine 24 and loading machine 26, increasing time between maintenance intervals, improving safety, and other such operational improvements and benefits. In one non-limiting example, the loading system controller 78 may be configured to identify the specific hauling machine 24 and the loading machine 26 being used at the jobsite 20. The loading system controller 78 may identify each machine through communication with the hauling machine control unit 34 and loading machine control unit 48. Moreover, the loading system controller 78 may have a database which includes a variety of hauling machine 24 and loading machine 26 parameters such as but not limited to, payload capacity, hauling capacity, and other such machine parameters.

Additionally, the loading system controller 78 may receive the payload body visual payload body visual data set collected by the one or more visual sensors 58 configured to scan the payload volume 60 of the hauling machine 24. Once received, the loading system controller 78 may be programmed to analyze the payload body visual data set and generate a payload body map of the payload body 36. The payload body map may show topographical features such as but not limited to, the surface topography and payload area of the payload body 36. Moreover, the payload body map may be analyzed to determine the available payload volume 60 of the payload body 36. In one non-limiting example, prior to the start of the loading sequence, the loading system controller 78 may analyze the payload body map generated from the payload body visual data set to confirm the payload body 36 is empty, such as illustrated in FIGS. 2a and 2b. Furthermore, the loading system controller 78 may be configured to transmit a signal if an undesirable condition is detected, such as the payload body 36 is not empty or contains material from a previous loading cycle (i.e., carryback) or other such condition. Furthermore, in some embodiments, the loading system controller 78 may reference the payload body map to program or otherwise generate a loading sequence for the loading machine 26 to follow during loading the payload body 36 of the hauling machine 24. The loading sequence may be transmitted or otherwise sent from the loading system controller 78 to the hauling machine control unit 34 and the loading machine control unit 48.

Moreover, in a manually operated system (i.e., operator occupied hauling machine 24 and loading machine 26), the loading sequence may be displayed on an operator display unit (not shown) located within the operator compartments 32, 46 of the hauling machine 24 and loading machine 26 to guide the operator to deliver the work material 37 to a first target dump zone 80 within the payload body 36 during the loading sequence. Alternatively, in an automated system (i.e., autonomous hauling machine 24 and loading machine 26), the loading sequence may be received by the hauling machine control unit 34 and loading machine control unit 48 and used to instruct and guide the loading machine 26 to autonomously deliver the work material 37 to the first target dump zone 80 within the payload body 36 of the hauling machine 24.

Referring now to FIG. 3 with continued reference to FIGS. 1-2, the hauling machine 24 and the loading machine 26 are illustrated operating around the jobsite 20 during the loading cycle. Furthermore, FIG. 3a shows a side view of the hauling machine 24 with a partial load of the work material 37 loaded into the payload body 36 and FIG. 3b shows a top view the hauling machine 24 with the partially filled payload body 36 and loading machine 26 with a filled payload bucket 50 operating around the jobsite 20. The one or more visual sensors 58 may be further configured to monitor and scan the payload body 36 and/or the payload bucket 50 during the loading cycle. For example, after the loading machine 26 loads the work material 37 into the first target dump zone 80, previously identified by the loading system controller 78 and communicated to the hauling machine 24 and the loading machine 26, the one or more visual sensors 58 may perform another scan of the payload body 36. As discussed above, the one or more visual sensors 58 may be mounted on the hauling machine 24, the loading machine 26 or both, and the one or more visual sensors 58 may include a camera, a RADAR scanning device, a LIDAR scanning device, a 3D scanning device, or other such device. Therefore, the one or more visual sensors 58 may be configured to scan the payload body 36 and the payload volume 60 to determine the state of the work material 37 placed in the hauling machine 24. In some embodiments, the one or more visual sensors 58 may collect an updated payload body visual data set which is communicated or otherwise transmitted to the hauling machine control unit 34 and/or the loading machine control unit 48. Moreover, the payload body visual data set may be further communicated from the hauling machine control unit 34 and/or the loading machine control unit 48 to the loading system controller 78 located in the back office operations center 76.

During the loading of the hauling machine 24, the loading machine 26 may also monitor the work material 37 which is scooped up by the payload bucket 50. The loading machine 26 may be configured with one or more additional sensors 66 mounted on the payload bucket 50, the, the attachment arms 52, or other location of the loading machine, and the one or more sensors 66 may be configured to determine the weight of the work material 37 in the payload bucket 50. Furthermore, as discussed above, one or more visual sensors 58 may be mounted on the loading machine 26 and configured to scan the payload bucket 50 to generate a loading bucket visual data set. In some embodiments, the loading bucket visual data set may be transmitted by the loading machine communication module 70 to the loading system controller 78. As a result, the loading system controller 78 may analyze the payload bucket visual data set and the data collected by the additional sensors 66 to determine the weight, volume, composition, or other such characteristic of the work material 37 scooped up by the loading machine 26 and contained within the payload bucket 50.

Following the placement of the first load of work material 37 in the first target dump zone 80 of the payload body 36, the loading system controller 78 may receive and analyze the updated payload body visual data set and generate an updated payload body map of the payload body 36. Furthermore, the loading system controller 78 may receive the payload bucket visual data set and data collected from the additional sensors 66 mounted on the loading machine 26. Based on the updated payload body visual data, payload bucket visual data, and data from the additional sensors 62, 66 the loading system controller 78 may analyze the condition of the of the work material 37 that is placed in the payload volume 60 of the payload body 36 and determine a second or additional target dump zone 82 for the work material 37. For example, the loading system controller 78 may reference the previously generated payload body map to determine whether the work material 37 was loaded into the correct location of the payload body (i.e., the first target dump zone 80). Moreover, the loading system controller 78 may then analyze the additional data received from the hauling machine 24 and loading machine 26 and determine a preferred or optimized location to place subsequent loads of work material (i.e., the second or additional target dump zone 82). In some embodiments, the loading system controller 78 may analyze the payload body visual data, the payload bucket visual data, and data from the additional sensors 62, 66 to search for any undesirable conditions of the payload body 36 and payload bucket 50 such as but not limited to, an imbalanced load, presence of large/oversized boulders, an overload condition, or other such conditions.

Referring now to FIG. 4, a schematic of a payload optimization system 84 is shown. The payload optimization system 84 may be configured to monitor and control work activities such as but not limited to, loading, hauling, unloading, and other associated activities of hauling and loading machines 24, 26 operating in and around the jobsite 20. In some embodiments, the payload optimization system 84 may include the loading system controller 78 which is programmed to send and receive data signals, control signals, and other information between the hauling machine 24, the loading machine 26 and other such equipment located around the jobsite 20. More specifically, the loading system controller 78 may be communicably coupled with equipment at the jobsite 20 through the wireless communication network 74 (i.e., Bluetooth network, near-field communication network, radio frequency communication network, computer data network, Wi-Fi data network, cellular data network, satellite data network, or other such data communication network). For example, the loading system controller 78 may include a loading system communication module 85 that communicates with the hauling machine communication module 68 and the loading machine communication module 70 over the wireless communication network 74. As a result, the loading system controller 78 may transmit operational commands to the hauling and loading machines 24, 26 which may provide a set of loading instructions for the optimal loading of work material 37 into the payload body 36.

The loading system controller 78 may include a microprocessor 86 for executing the software, programs, and/or algorithms that are configured to control, measure, and monitor the operation of the hauling machine 24 and the loading machine 26. Moreover, the microprocessor 86 may include a memory module 88 which further includes read-only memory (ROM) 90, configured to provide storage for the software, programs, algorithms, and other executable files. The memory module 88 may also include random access memory (RAM) 92, which provides storage space for the data generated during the execution of the software, programs, and/or algorithms. Furthermore, the memory module 88 may include a secondary storage module 93, such as but not limited to, a hard disk drive, a solid state drive, a flash drive, or other such data storage device. Additionally, the loading system controller 78 may be configured with software or other executable data files programmed to analyze and process the payload body visual data set and other data and machine information received from the hauling machine 24, and the loading machine 26. Furthermore, the loading system controller 78 may output or otherwise transmit a plurality of command and control signals to direct and optimize the loading of the hauling machine 24 based on the analysis and computation of the received visual data and other collected information. While the microprocessor 86 is illustrated in FIG. 3, it will be appreciated that other components such as but not limited to, a microcontroller, an application specific integrated circuit (ASIC), or other electronic device may be used to control and operate the loading system controller 78.

Furthermore, the loading system controller 78 may be operably coupled to an input/output module 94, and an operator of the payload optimization system 84 may use the input/output module 94 to access and selectively operate the loading system controller 78. For example, the input/output module 94 may be configured to allow the operator to input or execute commands to the loading system controller 78 through a keyboard, a mouse, a dial, a button, a joystick, a touch screen, a microphone, or other known input device. Additionally, data and other such information provided by the loading system controller 78 may be output to a display device such as but not limited to, a monitor, a speaker, a video screen, or other visual/audio display device capable of providing the output of the loading system controller 78 to the operator. In some embodiments, the input/output module 94 may be coupled to the loading system controller 78 through a wired connection and the input/output module 94 may be adjacently positioned to the loading system controller 78 in the back office operations center 76. Alternatively, the input/output module 94 may be coupled to the loading system controller 78 through a wireless communication network such as, a Bluetooth network, a near-field communication network, a radio frequency communication network, a computer data network, a Wi-Fi data network, a cellular data network, a satellite data network, or other such data communication network. Furthermore, the input/output module 94 may be configured as a handheld mobile device wirelessly connected to the loading system controller 78 such as but not limited to, a tablet computer, a smart phone, a cellular phone, a laptop computer, or other such mobile electronic device. As a result, the operator and the input/output module 94 may be remotely located from the loading system controller 78. In some embodiments, the input/output module 94 may be configured such that operator remotely communicates with the loading system controller 78 to control and monitor the payload optimization system 84 from a location other than the back office operations center 76. Moreover, a supervisor, planner, mechanic, autonomous control system, or other interested personnel or system may be able to access the loading system controller 78 from a separate input/output module 94 which remotely communicates with the loading system controller 78 to monitor and view the activity of the work machines 22.

During operation, the payload optimization system 84 may be configured to control, monitor and update the loading activities of the hauling and loading machine 24, 26 operating around the jobsite 20. In some embodiments, the hauling machine 24 may include the hauling machine control unit 34 that is coupled to the hauling machine communication module 68. In some embodiments, the hauling machine communication module 68 communicably couples the hauling machine 24 to the loading machine 26, the loading system controller 78 and other such communication devices located around the jobsite 20 that may be connected to the wireless network 74. Additionally, one or more visual sensors 58 (i.e., camera, RADAR, LIDAR, or 3D scanning device) may be attached to the hauling machine 24 and configured to scan and collect visual data of the payload body 36 (FIGS. 2 and 3). Furthermore, additional sensors 62 may be mounted at various locations around the hauling machine 24 and configured to collect operational data of the hauling machine 24. In one non-limiting example, additional sensors 62 may be mounted on the hauling machine suspension system 64 (FIGS. 2 and 3) and configured to measure and monitor the payload body 36 and other components of the hauling machine 24. In some embodiments, data collected by the one or more visual sensors 58 and the additional sensors 62 may be used together to determine the state or condition of the work material 37 (FIGS. 2 and 3) loaded into the payload body 36.

The one or more visual sensors 58 may be configured to scan the payload body 36 and collect the payload body visual data set. The payload body visual data set may be directly transmitted to a hauling machine display unit 96 mounted in the operator compartment 32 (FIGS. 1-3) of the hauling machine 24. As a result, the operator of the hauling machine 24 may be able to visually confirm the state of the work material 37 loaded in the payload body 36 (FIGS. 2 and 3). For example, the visual data set may display information indicating the payload body is empty, partially full, completely full, or other such information. Moreover, the visual data set collected by the one or more visual sensors 58 may be transmitted to the loading system controller 78 for further analysis. Data and information collected by the additional sensors 62 included on the hauling machine 24 may be combined with the visual data set to help the operator of the hauling machine 24 monitor the state or condition of the work material 37 in the payload body 36 (FIGS. 2 and 3). Data collected by the additional sensors 62 may be received by the hauling machine control unit 34 and communicated to the operator through the hauling machine display unit 96. Additionally, the hauling machine control unit 34 may transmit the visual data set, and information collected by the additional sensors 62 to the loading system controller 78 for further analysis.

The loading machine 26 may be similarly equipped with a loading machine control unit 48 that is coupled to the loading machine communication module 70. In some embodiments, the loading machine communication module 70 may communicably couple the loading machine 26 to the hauling machine 24, the loading system controller 78 and other such communication devices located around the jobsite 20 that may be connected to the wireless network 74. Furthermore, the loading machine may have one or more visual sensors 58 (i.e., camera, RADAR, LIDAR, or 3D scanning device) attached to the loading machine 26 and configured to scan the payload bucket 50. Furthermore, additional sensors 66 may be mounted at various locations around the loading machine 26 and configured to collect operational data of the loading machine 26. In one non-limiting example, additional sensors 66 may be mounted on the payload bucket 50 (FIGS. 2 and 3) and/or the attachment arms 52 and configured to measure and monitor the work material 37 weight and volume in the payload bucket 50. In some embodiments, data collected by the one or more visual sensors 58 and the additional sensors 66 may be used in combination to determine the state or condition of the work material 37 (FIGS. 2 and 3) loaded into the payload body 36.

The one or more visual sensors 58 may be configured to scan the payload bucket 50 and collect the payload bucket visual data set. The payload bucket visual data set may be directly fed to a loading machine display unit 98 mounted in the operator compartment 46 (FIGS. 1-3) of the loading machine 26. As a result, the operator of the loading machine 26 may be able to visually confirm the state of the work material 37 loaded in the payload bucket 50 (FIGS. 2 and 3). For example, the payload bucket visual data set may display information indicating the payload bucket is empty, partially full, completely full, or other such information. Additionally, the payload bucket visual data set may allow the operator of the loading machine 26 to view the composition of the work material 37. For example, the operator may be able to determine if the work material 37 includes large rocks, small rocks, gravel, loose dirt, or any other such material or combination thereof. Moreover, the payload bucket visual data set collected by the one or more visual sensors 58 may be transmitted by the loading machine communication module 70 to the loading system controller 78 for further analysis. In some embodiments, data and information collected by the additional sensors 66 included on the loading machine 26 may be combined with the payload bucket visual data set to help the operator of the loading machine 26 monitor the state or condition of the work material 37 in the payload bucket 50 (FIGS. 2 and 3). Data collected by the additional sensors 66 may be received by the loading machine control unit 48 and communicated to the operator through the loading machine display unit 98. Additionally, the hauling machine control unit 34 may transmit the payload bucket visual data set, and information collected by the additional sensors 66 to the loading system controller 78 for further analysis.

In some embodiments, the payload optimization system 84 may be configured such that the loading system controller 78, the hauling machine control unit 34 and the loading machine control unit 48 are all communicably coupled to one another and able to transmit and receive data from one another. The loading system controller 78 may be further configured to analyze data which is collected by the hauling machine 24 and loading machine 26 and generate a loading sequence plan for the hauling and loading machine 24, 26 to follow. As discussed above, the hauling machine 24 may be equipped with one or more visual sensors 58 configured to scan the payload body 36 of the hauling machine 24 and generate a payload body visual data set. Moreover, the loading machine 26 may be similarly equipped with one or more visual sensors 58 configured to scan the payload bucket 50 of the loading machine 26 and generate a payload bucket visual data set. Additionally, the hauling and loading machines 24, 26 may include additional sensors 62, 66 that are configured to monitor and collect data from other hauling and loading machine 24, 26 components and systems. The payload body visual data set, the payload bucket visual data set and other data and information collected by the hauling and loading machine 24, 26 may be transmitted to the loading system controller 78 for analysis and generation of a loading sequence to optimize loading of the hauling machine 24 by the loading machine 26.

The loading system controller 78 may save or otherwise store data and information received from the loading and hauling machines 24, 26 in the memory module 88 or other such storage location such as a cloud data storage location. In one non-limiting example, the loading system controller 78 may identify the hauling machine 24 and the loading machine 26 based on the data and information received from each machine. The loading system controller 78 may then be able to access a machine specification module 100, either stored locally on the loading system controller 78 or on another networked computing device. The machine specification module 100 may provide the loading system controller 78 with hauling and loading machine 24, 26 information such as but not limited to, capacity of the payload body 36, capacity of the payload bucket 50 and other such information. Additionally, the loading system controller 78 may include a payload mapping module 102 which may generate a payload map of the payload body 36 and/or payload bucket 50 based on the payload body visual data set, the payload bucket visual data set and other data received from the hauling and loading machines 24, 26. Furthermore, the loading system controller 78 may include a vision data module 103 which is configured to receive the payload body vision data set and the payload bucket vision data set and produce an optimized payload vision data set which may be used by the loading system controller 78 to optimize the loading operation of the hauling machine 24.

Prior to the start of a loading sequence, the payload map of the payload body 36 may be analyzed to confirm the payload body 36 is empty. In some embodiments, the loading system controller 78 may generate an operator alert or other such message if the analysis of the payload map determines the payload body 36 is not empty. Additionally, the payload volume 60 of the payload body 36 may be determined from the payload map analysis. As a result, the loading system controller 78 may be able to calculate or otherwise determine how much work material 37 can be loaded into the payload body 36 of the hauling machine 24. The loading system controller 78 may also analyze data received from the additional sensors 62 coupled to the hauling machine suspension system 64 or other machine systems to determine the state and hauling capabilities of the payload body 36.

In some embodiments, the loading system controller 78 may further include a loading sequence module 104 which uses the payload map analysis and other information received from the hauling machine 24 and the loading machine 26 to generate a set of loading sequence instructions. Additionally, the loading system controller 78 may reference hauling and loading machine 24, 26 specifications from the machine specification module and incorporate this information into the loading sequence instructions. Once the loading sequence is determined, the loading system controller 78 may transmit the set of operational instructions to the loading machine 26, the hauling machine 24 and any other machine involved in the loading operation. Furthermore, once the loading sequence begins, the hauling and loading machines 24, 26 may continue to scan the payload body 36 and payload bucket 50 and transmit an updated payload body visual data, an updated payload bucket visual data, and any other data collected by the additional sensors 62, 66 and machine systems. As a result, the loading system controller 78 may analyze the updated data and generate an updated payload body map to confirm that the loading sequence is properly progressing. In some embodiments, the loading system controller 78 may issue a corrected loading sequence if abnormal payload conditions such as but not limited to, unequal load distribution, improper work material 37 placement or other such abnormal condition. Alternatively, if the corrected loading sequence is unable to correct the deviation from the loading sequence then the loading system controller 78 may signal the hauling and loading machines 24, 26 to pause the loading sequence so the problems may be corrected.

The loading system controller may also be configured with a machine parameter monitoring module 105 that is configured to receive data and information collected from other monitoring systems of the hauling machine 24 and the loading machine 26. For example, the machine parameter monitoring module 105 may include a pressure sensing module configured to receive data collected by the sensors 62 mounted on the hauling machine suspension system 64. Additionally, the machine parameter monitoring module 105 may also include a payload monitoring module configured to receive data collected by the sensors 66 mounted on the loading machine 26 configured to measure the load weight and/or density of the work material 37 contained in the payload bucket 50.

Moreover, the payload optimization system 84 may be configured to operate in two or more operational modes. In a first mode, the hauling and loading machines 24, 26 may be configured to operate in a manual or semi-automatic mode which may require an operator to control and maneuver the hauling and loading machines 24, 26. In the semi-automatic mode, the loading system controller 78 may generate the set of loading sequence instructions and transmit the instructions to the hauling and loading machines 24, 26. In some embodiments, the received loading instructions may be received by the hauling machine control unit 34 and the loading machine control unit 48 and displayed to the operators of the hauling and loading machine 24, 26. Moreover, the loading machine display unit 98 may show or otherwise instruct the operator where a specific load of work material 37 should be placed in the payload body 36 (i.e., first target dump zone 80, second or additional target dump zone 82). Additionally, in the semi-automatic mode the loading system controller 78 may continuously update the loading sequence instructions such that anytime the loading system controller 78 determines a correction to the loading sequence is needed, updated instructions will be sent to the hauling and loading machine 24, 26.

Alternatively, in a second mode, the payload optimization system 84 may be configured to operate in a fully autonomous mode which may not require the physical presence of the operator in the operator compartments 32, 46 of the hauling and loading machines 24, 26. In the fully autonomous mode the hauling and loading machines 24, 26 may be equipped with additional sensors 62, 66 and other machine intelligence that is configured to autonomously control and operate the hauling and loading machines 24, 26 around the jobsite 20. In one non-limiting example, the hauling machine control unit 34 and the loading machine control unit 48 may be selectably configured to activate and/or deactivate the operation of the semi-automatic and fully autonomous mode. However, other configurations of the hauling and loading machine 24, 26 are possible. Moreover, in the fully autonomous mode, the loading system controller 78 may still generate the set of loading sequence instructions and transmit the instructions to the hauling and loading machine 24, 26. Once received, the hauling machine control unit 34 and loading machine control unit 48 may transmit the loading instructions to the autonomous guidance system in the hauling and loading machine 24, 26 and the guidance system will guide the loading machine 26 to place the work material 37 in the desired payload body 36 location (i.e., first target dump zone 80, second or additional target dump zone 82). Additionally, in the fully autonomous mode the loading system controller 78 may continuously update the loading sequence instructions such that anytime the loading system controller 78 determines a correction to the loading sequence is needed, updated instructions will be sent to the hauling and loading machine 24, 26 and executed by the autonomous guidance system.

Additionally, the secondary storage module 93 in the memory module 88 may be configured to save data received from the one or more visual sensors 58, the additional sensors 62, 66 on the hauling and loading machines 24, 26, the hauling machine control unit 34, the loading machine control unit 48, and other machine systems and components to create a historical operational data set of the hauling and loading machines 24, 26. Moreover, the loading system controller 78 may save and log any corrective action control signals or updates to the loading sequence instructions transmitted to the hauling and loading machines 24, 26. In some embodiments, the loading system controller 78 and other components of the payload optimization system 84 may be further configured to analyze the historical data set saved on the loading system controller 78 to identify any operational trends or other signals which may allow the payload optimization system 84 to predict when abnormal loading and/or hauling conditions may occur. Furthermore, the payload optimization system 84 may be able to adaptively adjust or further optimize the loading sequence instructions based on the analysis of the historical data set.

INDUSTRIAL APPLICABILITY

In general, the present disclosure may find application in many industries, including but not limited to, mining, construction, agriculture, and other such industries. In some embodiments, the hauling and loading machines 24, 26 may be configured to work together around a jobsite 20. Additionally, one or more visual sensors 58 may be mounted on the hauling and loading machines 24, 24 and the one or more visual sensors 58 may be configured to scan and monitor the payload body 36 of the hauling machine 24 and payload bucket 50 of the loading machine 26. Furthermore, during a loading operation performed by the hauling and loading machines 24, 26, the payload optimization system 84 may be configured to monitor, control, and optimize the loading of work material 37 into the payload body 36 of the hauling machine 24. More specifically, the payload optimization system 84 may generate a set of loading instructions for the loading machine 24 to follow while loading the work material into the payload body 36 of the hauling machine 24. Furthermore, the payload optimization system 84 may be electronically and communicably coupled with the hauling and loading machines 24, 26 such that the loading system controller 78 of the payload optimization system may monitor and update the set of loading sequence instructions in real time to ensure the work material 37 is optimally loaded into the hauling machine 24 and transported to its desired location.

Referring to FIG. 5, with continued reference to FIGS. 1-4, a method 106 for optimally loading the hauling machine 24 is shown. In a first block 108 of the method 106, the payload optimization system 84 may identify the hauling and loading machine 24, 26 present at the jobsite 20 and ready to start a new loading sequence. In one non-limiting example, the payload optimization system 84 may use an identification signal or other such identifier sent from the hauling and loading machine 24, 26 and received by the loading system controller 78 to identify each machine. Once the hauling and loading machine 24, 26 are identified, then in a next block 110 the payload capacity of the hauling machine 24 and the loading capacity of the loading machine 26 may be determined. In some embodiments, the loading system controller 78 may use the machine identification to reference the machine specification module 100. The machine specification module 100 may contain information for the hauling and loading machines 24, 26, such as but not limited to hauling capacity, loading capacity and other such machine specifications. Additionally or alternatively, an operator or other individual may input or otherwise provide the hauling capacity and loading capacity of the hauling and loading machines 24, 26.

Once the hauling and loading capacity is determined, then in a next block 112 the payload body 36 of the hauling machine may be visually scanned by one or more visual sensors 58 mounted on the hauling machine 24. The one or more visual sensors 58 may be a camera, a RADAR scanning device, a LIDAR scanning device, a 3D scanning device, or other such scanning device which is configured to scan the payload body 36. Moreover, the one or more visual sensors 58 may produce a payload body visual data set which is transmitted to the loading system controller 78 located in the back office operations center 76 or other such location. The loading system controller 78 may analyze the payload body visual data set to determine the condition of the payload body 36 (i.e., empty, partially full, or full). Typically, the optimized loading of the hauling machine 24 will not begin until the payload body 36 is confirmed to be empty and otherwise ready to receive a load of work material 37. Additionally, the hauling machine may be configured with additional sensors 62 coupled to cylinders or other components of the hauling machine suspension system 64. The information collected by the additional sensors 62 may also be transmitted to the loading system controller 78 and used along with the payload body visual data set to determine the condition of the payload body 36 (i.e., empty, partially full, or full).

Once the hauling machine 24 is ready to be loaded, a signal may be sent from the loading system controller 78 to the loading machine 26 to begin the loading sequence. In a next block 114, the loading machine 26 scoops or otherwise fills the payload bucket 50 with work material 37 located at the jobsite 20. In some embodiments, the loading machine 26 may also have one or more visual sensors 58 (i.e., camera, RADAR scanning device, LIDAR scanning device, 3D scanning device) attached to the payload bucket 50 or other component of the loading machine 26. The one or more visual sensors 58 may be configured to scan the payload bucket 50 and produce a payload visual data set. The loading machine may also have additional sensors 66 mounted to the payload bucket 50, the attachment arms 52, and/or other such location. The additional sensors 66 may be configured to collect the weight, density, or other such measurement of the work material 37 present in the payload bucket 50. The loading machine 26 may then transmit the payload bucket visual data set and the additional sensor 66 data to the loading system controller 78.

In a next block 116, the loading system controller 78 may analyze the payload body visual data, the additional sensor 62 data, the payload bucket visual data set, and the additional sensor 66 data received from the hauling and loading machines 24, 26. In some embodiments, the loading system controller 78 may first create a payload map of the payload body 36 based on the payload body visual data and additional sensor 62 data. Moreover, the loading system controller 78 may then use the payload map along with the data received from the hauling and loading machines 24, 26 to generate a set of loading sequence instructions for the hauling and loading machines 24, 26. In some embodiments, the set of loading sequence instructions may be optimized to produce benefits and improvements such as but not limited to, the efficiency of loading the hauling machine 24 is improved, excess wear on the hauling and loading machines 24, 26 is reduced, fuel consumption is reduced, and safety is improved. Additionally, optimizing the loading sequence may help reduce the number of loading cycles (i.e., filling payload bucket 50 and dumping in payload body 36), minimize excess movements of the hauling and loading machines 24, 26, reduce the over filling or under filling the payload body 36 and other such improvements.

After the loading system controller 78 generates the set of loading sequence instructions, then in a next block 118 the instructions may be transmitted to the hauling and loading machines 24, 26. In one non-limiting example the payload optimization system 84 may be used to optimize the hauling and loading machine 24, 26 which operate in a semi-automatic mode. In the semi-automatic mode, an operator is in the operator compartment 32, 46 of the hauling and loading machine 24, 26 and operates the hauling and loading machine 24, 26 during loading. Moreover, the set of loading sequence instructions may be transmitted from the loading system controller 78 to the hauling machine control unit 34 and the loading machine control unit 48 and the commands and/or instructions may be displayed on the hauling and loading machine display units 96, 98. More specifically, the operator of the loading machine 26 may view the instructions sent by the loading system controller 78 and load the work material 37 in the designated location (i.e., the first target dump location 80) of the payload body 36. Alternatively, the payload optimization system 84 may be used to optimize the hauling and loading machine 24, 26 which operate in a fully autonomous mode. In the fully autonomous mode, the hauling and loading machine 24, 26 are not operated by an operator manipulating the controls of each machine. Rather, the hauling and loading machine 24, 26 are automatically controlled and guided by on-board machine intelligence and a variety of sensors. As a result, the set of loading sequence instructions may be sent from the loading system controller 78 to the hauling and loading machine control units 34, 48. Moreover, the loading machine control unit 48 may receive the set of loading sequence instructions and the fully autonomous control system will guide the loading machine 26 during the loading sequence.

Once the hauling and loading machine 24, 26 receive set of loading sequence instructions, then in a next block 120 the loading machine 26 may dump the work material 37 from the payload bucket 50 into the designated location (i.e., first target dump location 80) of the payload body 36. Moreover, the set of loading sequence instructions may specify the first target dump location 80 for the loading machine 26 to dump the work material 37 based on the payload body visual data set, the payload bucket visual data set and additional sensor data 62, 66 provided by the hauling and loading machine 24, 26. After the loading machine 26 dumps the work material 37 in the first target dump location 80, then in a next block 122 the one or more visual sensors 58 on the hauling machine 24 may scan the payload body 36 and collect an updated payload body visual data set. Moreover, the additional sensors 62 coupled to the hauling machine suspension system 64 may continue to collect additional data and information. The hauling machine 24 may then transmit the payload body visual data set and the additional sensor 62 data to the loading system controller 78. Furthermore, the loading machine 26 may have scooped up an additional load of work material 37 and the one or more visual sensors 58 on the loading machine 26 may scan the payload bucket 50 and collect an updated payload bucket visual data set. The additional sensors 66 on the payload bucket 50 may continue to collect additional data and information related to the weight of the work material 37 picked up by the payload bucket 50. The loading machine 26 may transmit the updated payload bucket visual data set and the additional sensor 66 data to the loading system controller 78.

After the loading system controller 78 receives the data from the hauling and loading machines 24, 26 it may analyze the received data to determine if the first load of work material 37 was optimally placed in the first target dump zone 80. If, in a next block 124, the work material 37 was determined to be optimally placed in the first target dump zone 80 and the work material 37 in the payload body 36 is properly distributed (i.e., fore-aft distribution and side to side distribution) then the loading system controller 78 may determine the state of the payload body 36 (i.e., empty, partially full, completely full). If, in a next block 126, the loading system controller 78 determines the payload body 36 is partially full, then the loading system controller 78 determine the payload body 36 may accept an additional load of work material 37. As a result, the loading system controller 78 may designate a second or additional target dump zone 82 in the payload body 36 and the method 106 may return to block 114. The payload optimization system 84 may repeat the subsequent steps to continue loading the payload body 36. Alternatively, if in block 128, the loading system controller 78 determines the payload body 36 is full, then the loading sequence may be terminated and the hauling machine 24 may dump or otherwise deliver the load. Furthermore, when the payload body 36 is determined to be full, the loading system controller 78 may analyze the data received from the hauling and loading machines 24, 26 to determine whether the payload body 36 is overloaded or overfilled. In some embodiments, if the payload body 36 is determined to be overloaded or overfilled, the loading system controller 78 may send a corrective action signal to remove, redistribute, or other such corrective action that may correct the overloaded or overfilled condition of the payload body 36.

Alternatively, after the loading system controller receives the data from the hauling and loading machines 24, 26, it may determine that the first load of work material 37 was not optimally placed in the first target dump zone 80. In a next block, 130 the payload system controller 78 may signal that the load placement was not ok and continue to analyze the state of the work material 37 in the payload body 36. If, in block 132, the payload system controller 78 determines that a corrective action is possible to fix the payload placement, then the payload system controller 78 may issue a corrective action such as but not limited to, dozing is needed, abnormal size boulder detected, or other such corrective action. Moreover, the payload system controller 78 may update or correct the set of loading sequence instructions sent to the loading machine 26 in attempt to correct the payload condition. Once the issue has been corrected, the loading system controller 78 may designate a second or additional target dump zone 82 in the payload body 36 and the method 106 may return to block 114. The payload optimization system 84 may repeat the subsequent steps to continue loading the payload body 36. However, if in block 134, the payload system controller 78 determines that a corrective action is not possible to fix the payload placement, then the loading system controller 78 may issue a signal that the current loading sequence should be aborted, the payload body 36 should be dumped, and the sequence should start over.

While the foregoing detailed description has been given and provided with respect to certain specific embodiments, it is to be understood that the scope of the disclosure should not be limited to such embodiments, but that the same are provided simply for enablement and best mode purposes. The breadth and spirit of the present disclosure is broader than the embodiments specifically disclosed and encompassed within the claims appended hereto. Moreover, while some features are described in conjunction with certain specific embodiments, these features are not limited to use with only the embodiment with which they are described, but instead may be used together with or separate from, other features disclosed in conjunction with alternate embodiments.

REALTIME PAYLOAD MAPPING FOR LOADER/HAULER SYSTEM OPTIMIZATION

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