Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This communication is a Final Office Action in response to Applicant’s amendment for application number 18/181,452 received on 01/20/2026.
In accordance with Applicant’s amendment. Claims 1-8, 10-20, and 22 are amended, currently pending, and have been examined.
Response to Amendment
The amendment filed on 01/20/2026 has been entered.
Applicant’s amendment necessitated the new ground(s) of rejection set forth in this Office Action.
Response to Arguments
Response to §103 arguments – Applicant’s arguments with respect to the §103 rejections previously applied to the claims are raised in support of the amendments, which necessitated new ground(s) of rejection, and which are believed to be fully addressed in the updated §103 rejections below.
Claim Rejections - 35 USC § 103
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 8, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Humphrey (US 20160342915 A1, hereinafter “Humphrey”), in view of Grambihler et al. (US 20210325899 A1, hereinafter “Grambihler”), in further view of Nettleton et al. (WO 2010124336 A1, hereinafter “Nettleton”).
Regarding Claim 1: Humphrey teaches a computer-implemented method ([0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.) with limitations for:
receiving, by a fleet management controller, processing plant data from a plant management controller associated with a processing plant, ([0003] a dispatching system for controlling the vehicles within a mine may be used to optimize material transport and reduce costs.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.; [0006] In another aspect, this disclosure describes a system for managing a fleet of vehicles, the system comprising a work site comprising a plurality of vehicles; a plurality of autonomous vehicles, each autonomous vehicle comprising an electronic processing unit configured to transmit data to a second location; a first location with an electronic processing unit configured to transmit data to the second location; and the second location with an electronic processing unit configured to determine, in response to the data transmitted by the plurality of autonomous vehicles and the first location, whether the first location is available to service a vehicle, the electronic processing unit of the second location is further configured to dispatch at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and to deactivate at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.);
the fleet management controller is configured to dynamically control first operations of a fleet of autonomous machines, the first operations comprising the fleet of autonomous machines autonomously delivering loads of material to the processing plant, based at least in part on second operations of the processing plant indicated by the processing plant data received from the plant management controller, ([0003] a dispatching system for controlling the vehicles within a mine may be used to optimize material transport and reduce costs. For example, vehicles may include an articulating truck, a haul truck, a personnel carrier, a remix truck, a shuttle car, or a water truck. For example, a mining site may have multiple shovels and multiple processing sites.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.; [0020] autonomous vehicle 104 to travel to the processing site 110 and the route the autonomous vehicle 104 may take to travel from the shovel 108 to the processing site 110;
the plant management controller is configured to dynamically control the second operations of the processing plant, the second operations comprising one or more crushers of the processing plant processing the loads of material delivered by the fleet of autonomous machines, ([0002] This model has particular application in the mining industry, where material transportation involves a vehicle picking up a load of ore from a shovel site and transporting that ore to a processing site.; [0003] A processing site, broadly defined, encompasses any machine which may process mined ore or other materials delivered to it. For example, a processing site may include crusher machines; [0022] The computing system located at a shovel 108 also comprises a processor, one or more inputs, one or more outputs, a memory, and one or more transceivers. For example, if the shovel 108 is not operating in the manner it was designed to operate, the one or more outputs may display a user information or an alert that the shovel 108 is not operating in the manner it was designed to operate. For example, the shovel 108 may have become broken. The memory may comprise a computer readable memory to store instructions the processor may execute, according to one aspect of this disclosure. The instructions the processor may execute are further described herein.; [0023] The processing site 110 has a computing system similar to that of shovel 108 and it operates in a similar manner.; [0030] One way a processing site 110 may service a vehicle 104 or 106 is to unload the material the vehicle 104 or 106 may be transporting. The performance metrics may be instantaneous. For example, the shovel 108 may time how long it is taking to load the vehicle 104 or 106 it is currently servicing. Also, the processing site 110 may time how long it is taking to unload the vehicle 104 or 106 it is currently servicing. Alternatively, or additionally, to collecting instantaneous performance metrics is to store historical performance metrics. Once the shovel 108 or processing site 110 has collected the performance metrics, the method may proceed to step 506.);
based at least in part on material load data received from the fleet management controller, ([0023] The processing site 110 has a computing system similar to that of shovel 108 and it operates in a similar manner.; [0032] For example, the shovel 108 may perform work more slowly because, for example, the shovel 108 may be mining a harder block.);
generating, by the fleet management controller, machine instructions that dynamically adjust the first operations of the fleet of autonomous machines: in response to the second operations of the processing plant indicated by the processing plant data received from the plant management controller, ([0062] At 710, the processor 302 determines whether any of the autonomous vehicles 104 or the non-autonomous vehicles 106 may currently be bunching together or may bunch together in the future. Vehicle bunching indicates that there are too many vehicles 104 and 106 active within the work site 100. Therefore, the work site 100 is incurring extra costs by using extra vehicles 104 and 106 which do not increase the productivity of the work site 100. The processor 302 may determine that there is vehicle bunching by, for example, using the state, location, and travel information provided by the vehicles 104 and 106. For example, there may be more than one vehicle 104 or 106 waiting to service a shovel 108 or a processing site 110. The processor 302 may interpret this situation as evidence of vehicle bunching. If the processor 302 determines that there is vehicle bunching, the method may proceed to 714.; [0063] At 714, the processor 302 may transmit instructions to one of the autonomous vehicles 104 to discontinue serving the shovel 108 or processing site 110. If the autonomous vehicle 104 is not carrying material, the transmitted instructions may include instructions to follow a different route to a location where the autonomous vehicle 104 may become idle. Alternatively, if the autonomous vehicle 104 is transporting material, the transmitted instructions may include instructions to complete transporting the materials.; [0064] Returning to 710, if the processor 302 determines that there is no vehicle bunching, the method may proceed to 712.; [0065] At 712, since there are no available shovels 108 or processing sites 110 and there is no vehicle bunching, the processor 302 does not change the operation of the work site 100. For example, since there are no available shovels 108 or processing sites 110, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to activate and follow a route to an available shovel 108 or processing site 110, as explained above. Additionally, since there may be no vehicle bunching within the work site 100, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to become idle, as explained above.);
and to cause the fleet of autonomous machines to deliver particular loads of material, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0032] the shovel 108 loads vehicles 104 and 106 with material, such as mined ore.);
comprising material having particular attributes associated with the material blends indicated by the material target data, to the one or more crushers; ([0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste.; [0033] For example, the processing site 110 may perform work more slowly because, for example, the type of material it is unloading.; [0003] For example, a processing site may include crusher machines, waste storage sites, or ore storage sites.);
causing, by the fleet management controller, the fleet of autonomous machines to autonomously perform the first operations, dynamically adjusted in response to the second operations of the processing plant, by wirelessly sending the machine instructions to the fleet of autonomous machines; ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.).
Humphrey doesn’t explicitly teach:
wherein: the fleet management controller and the plant management controller are executed via different computing systems,
and the processing plant data, indicative of the second operations of the processing plant, comprises material target data indicating material blends processed by the one or more crushers;
and providing, by the fleet management controller to the plant management controller, the material load data, wherein the material load data indicates respective contents of the particular loads of material to be delivered to the one or more crushers by the fleet of autonomous machines based on the machine instructions.
Grambihler teaches:
and the processing plant data, indicative of the second operations of the processing plant, comprises material target data indicating material blends processed by the one or more crushers; ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing.; [0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed.);
and providing, by the fleet management controller to the plant management controller, the material load data, wherein the material load data indicates respective contents of the particular loads of material to be delivered to the one or more crushers by the fleet of autonomous machines based on the machine instructions. ([0028] the worksite management computing device 106 determines the location for the hauling machine 102 to discharge the load based on the material data (e.g., type, composition, characteristics, etc.) associated with the load (e.g., material loaded in the hauling machine 102. In such examples, the worksite management computing device 106 accesses the worksite data 114 to determine the material data associated with material loaded into a hauling machine and determines a discharge location 130 based on the material data. For example, a worksite management computing device 106 determines, based on worksite data 114, that a hauling machine is loaded with leach material. Based on the determination that the load includes leach material, the worksite management computing device 106 determines a location associated with a leach field for the hauling machine 102 to discharge the load. For another example, a worksite management computing device 106 determines, based on worksite data 114, that a hauling machine is loaded with overburden material. Based on the determination that the load includes overburden material, the worksite management computing device 106 sends an instruction to the hauling machine computing device 120 for the hauling machine 102 to discharge the load at the overburden pile 112.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to send an instruction to a hauling machine computing device 120 associated with the hauling machine 102(c) (not illustrated) to deliver the ore to the crushing machine 104 (Grambihler; [0029]). By incorporating the teachings of Grambihler, one would’ve been able to use material data to understand the characteristics of the material that will be processed and deliver the material based, in part, on the material load data.
Grambihler doesn’t explicitly teach:
wherein: the fleet management controller and the plant management controller are executed via different computing systems,
Nettleton teaches:
wherein: the fleet management controller and the plant management controller are executed via different computing systems, ([Abstract] The autonomous entity is instructed to move into a transition zone (906, 907) that spans the first zone and the second zone, wherein the autonomous entity while located in the first zone is responsive to supervisory control of a first controller (912) associated with the first zone. The autonomous entity is registered with a second controller (910) associated with the second zone to enable the autonomous entity to respond to supervisory control of the second controller as the autonomous entity enters the second zone through the transition zone.; [Column 1, Lines 6-7] The invention has various applications and, in one of its possible embodiments, has application to a mine automation system; [Column 1, Lines 14-27] One example of a complex application where autonomous operations may be used is in mining. Conventional open pit mining, for example of metal-bearing mineral or rock, normally involves the progressive accessing of an ore body followed by drilling, blasting, loading and haulage of the released material. In the case of iron ore it is mined in large blocks from a series of benches and the various mining activities (other than blasting) are performed concurrently, resulting in diverse equipment, and often personnel, being present simultaneously in the mine site. A bench of ore typically 40m long x 20m deep χ10m high and containing in the order of 8 kilotonnes of ore is first drilled to form a pattern of blast holes and the drilling residue is analysed, as one step in a more extensive analysis, to determine whether the material to be blasted comprises, on average, high grade ore, low grade ore or waste material. The blasted material is collected by shovels, excavators and/or front end haul loaders, loaded into haul trucks and transported from the mine pit.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Nettleton’s features listed above. One would’ve been motivated to do so, so the material is then processed outside of the mine pit, depending upon grade determination (Nettleton; [Column 1, Lines 27-28]). By incorporating the teachings of Nettleton, one would’ve been able to use separate controllers, executed via different computing systems, to control the different operations.
Regarding Claim 2: Humphrey doesn’t explicitly teach:
wherein: the material load data causes the plant management controller to dynamically adjust the second operations of the processing plant, based at least in part on the material load data, prior to delivery of the particular loads of material to the one or more crushers.
Grambihler teaches:
wherein: the material load data causes the plant management controller to dynamically adjust the second operations of the processing plant, based at least in part on the material load data, prior to delivery of the particular loads of material to the one or more crushers. ([0001] More specifically, the present disclosure relates to systems and methods for determining a discharge rate of the dumping machine based at least in part on a material to be discharged and/or a capability or capacity of a receiving machine (e.g., crusher).; [0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing.; [0076] In some examples, the computing device(s) 406 determines the discharge rate based on a capability of the receiving machine 404. In such examples, the discharge rate is based on the amount of material the crushing machine 404 can process (e.g., tons per hour, etc.). In some examples, the capability of the crushing machine 404 is determined based on a type of machine associated with the crusher and/or specifications associated therewith. For example, a j aw crusher is configured to process material at a first rate and a gyratory crusher is configured to process material at a second rate.; [0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed.); [0086] At operation 520, the processor causes the bed 514 to raise to an angle greater than the threshold angle based on a determination that the hauling machine 504 is within a second threshold distance of the discharge location 518. In various examples, the processor causes the bed to raise to a discharge angle 522 and/or at a discharge angle rate 524 associated with a particular discharge rate. As discussed above, the discharge rate may be determined based on the discharge location 518, the crusher 510 capacity and/or capability, a fuel capacity associated with the hauling machine 504, a desired fuel efficiency in material discharge (e.g., fuel efficient discharge rate selected), material data associated with the material in the bed 514, and the like.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to optimize performance of the receiving machine 404 (Grambihler; [0078]). By incorporating the teachings of Grambihler, one would’ve been able to modify second operations based at least in part on material data.
Regarding Claim 3: Humphrey doesn’t explicitly teach:
wherein the processing plant data comprises crusher operational data, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers, current bin fullness levels of the one or more crushers, threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers.
Grambihler teaches:
wherein the processing plant data comprises crusher operational data, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers, ([0131] historical data 936 and the historical data 938 include data associated with servicing (e.g., maintenance history) the crushing machine(s) 104 and the hauling machine(s) 102, respectively, and/or other data associated with the functioning of the crushing machine(s) 104 and the hauling machine(s) 102, respectively.); current bin fullness levels of the one or more crushers, ([Fig. 4] step 410: Receive, from a crusher computing device, sensor data associated with an amount of material in the crusher; [0021] the capacity of the discharge location may be determined, at least in part on sensor data associated with a receiving machine (e.g., crushing machine 104); [0032] the crushing machine computing device 122 sends the current capacity to the worksite management computing device 106 in real-time or near real-time); threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers. ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing. The worksite management computing device 106 receives second sensor data at a second time from the capacity sensor 118 and determines that, at the second time, a second amount of material in the crushing machine is above a second threshold amount.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to decrease the discharge rate of material from the hauling machine based on the second amount of material (Grambihler; [0026]). By incorporating the teachings of Grambihler, one would’ve been able to use crushing machine data to make decisions.
Regarding Claim 4: Humphrey doesn’t explicitly teach:
wherein the processing plant data comprises material processing rate data indicating one or more of: current material processing rates of the one or more crushers, or changes to material processing rates of the one or more crushers over a period of time.
Grambihler teaches:
wherein the processing plant data comprises material processing rate data indicating one or more of: current material processing rates of the one or more crushers, ([0031] a second crushing machine 104 is configured to process large rocks at a rate of approximately 10 tons per hour.); or changes to material processing rates of the one or more crushers over a period of time. ([0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed. In such examples, the amount of material that the crushing machine 404 can process over a time period (e.g., tons per hour) is based in part on a type, composition, and/or characteristic associated with the material. For example, a crushing machine 404 processes 10 tons of large rocks per hour and 20 tons of medium sized rocks per hour.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to optimize performance of the receiving machine 404 (Grambihler; [0078]). By incorporating the teachings of Grambihler, one would’ve been able to modify processing rates of material based on the capacity of the crushers.
Regarding Claim 5: Humphrey doesn’t explicitly teach:
wherein the material target data indicates one or more material modifiers defining one or more of material sizes or material moisture content levels associated with the material blends processed by the one or more crushers.
Grambihler teaches:
wherein the material target data indicates one or more material modifiers defining one or more of material sizes or material moisture content levels associated with the material blends processed by the one or more crushers. ([0022] the attributes of the material include a composition thereof, such as a percentage of ore, a grade of ore, and the like. In some examples, the attributes of the material include other physical and/or chemical characteristics of the material, such as mineral and/or chemical composition, density, particle volume, cohesiveness (e.g., tendency of material to stick together), hardness, fragmentation, permeability, texture, particle size, and the like. The listed attributes include illustrative examples and are not intended to be limiting; other attributes of the material are contemplated herein. [0024] The worksite data 114 includes material data (e.g., the type, composition and/or characteristic(s) of the material at the worksite 108).).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to determine a type and composition of material extracted from the particular mine proximate the source location and loaded into hauling machines 102 at the source location (Grambihler; [0024]). By incorporating the teachings of Grambihler, one would’ve been able to use material data to to indicate one or more material modifiers.
Regarding Claim 6: Humphrey doesn’t explicitly teach:
wherein the processing plant data comprises stockpile data indicating fullness levels of one or more stockpiles of the material the processing plant has available to process.
Grambihler teaches:
wherein the processing plant data comprises stockpile data indicating fullness levels of one or more stockpiles of the material the processing plant has available to process. ([0075] the computing device(s) 406 determine the discharge rate based on a current level of material in the receiving machine 404.
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to determine that the crushing machine 404 is capable of receiving material (Grambihler; [0075]). By incorporating the teachings of Grambihler, one would’ve been able to use track fullness level of the stockpiles of material at the processing plant.
Regarding Claim 8: Humphrey doesn’t explicitly teach:
wherein: the processing plant data indicates, to the fleet management controller, a decrease in a material processing rate of the one or more crushers over a period of time,
and the machine instructions adjust the first operations to reduce a material delivery rate, associated with the fleet of autonomous machines autonomously delivering the loads of material to the processing plant, to correspond with the decrease in the material processing rate.
Grambihler teaches:
wherein: the processing plant data indicates, to the fleet management controller, a decrease in a material processing rate of the one or more crushers over a period of time, ([0026] The worksite management computing device 106 continues to monitor an amount of material associated with the crushing machine 104 based on the sensor data, and continues to increase and/or decrease the discharge rate from the hauling machine 102 based on the sensor data until receiving an indication from the hauling machine 102 that a transfer of material is complete.);
and the machine instructions adjust the first operations to reduce a material delivery rate, associated with the fleet of autonomous machines autonomously delivering the loads of material to the processing plant, to correspond with the decrease in the material processing rate. ([0020] The hauling machine(s) 102 may be autonomous, semi-autonomous, or manually operated machines.; [0047] the hauling machine computing device 120 sends a command to the bed angle controller 134 to begin raising the bed to a threshold angle (e.g., 15 degrees, 20 degrees). The threshold angle includes an angle at which material will not be discharged from the bed of the hauling machine 102.; [0033] Based on the current capacity, the rate determination component 126 may determine that a slower discharge rate (e.g., 30 tons per hour less) will avoid overloading the crushing machine 104. One of ordinary skill in the art would reasonably interpret the commands to set the bed at a specific angle as equivalent to an adjustment to the material delivery operation based on the capacity of the receiving machine.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s additional features listed above. One would’ve been motivated to do so in order to determine the discharge rate for a current load (Grambihler; [0034]). By incorporating the teachings of Grambihler, one would’ve been able to adjust operations based on the current capacity of a crusher.
Regarding Claim 22: Humphrey teaches:
wherein: the fleet of autonomous machines comprises one or more autonomous haul trucks, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.);
causing the fleet of autonomous machines to autonomously perform the first operations comprises causing, via the machine instructions, a first autonomous haul truck of the one or more autonomous haul trucks to autonomously ([0021] Such instructions may include deploying one or more autonomous vehicles 104 or extracting one or more autonomous vehicles 104 from the work site 100): accept a first load of material ([0002] material transportation involves a vehicle picking up a load of ore from a shovel site and transporting that ore to a processing site.), having first attributes associated with a particular material blend processed by a particular crusher indicated by the material target data, at a first location at a worksite ([0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste.);
travel from the first location to the particular crusher at the processing plant ([0026] The routing instructions may instruct the autonomous vehicle 104 to travel along a given route to a shovel 108 or a processing site 110.; [0003] a processing site may include crusher machines);
and deliver the first load of material to the particular crusher ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.),
and the material load data, provided by the fleet management controller to the plant management controller, indicates the first attributes of the first load of material to be delivered by the first autonomous haul truck to the particular crusher. ([0002] where material transportation involves a vehicle picking up a load of ore from a shovel site and transporting that ore to a processing site.; [0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste.).
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Humphrey (US 20160342915 A1, hereinafter “Humphrey”), in view of Grambihler et al. (US 20210325899 A1, hereinafter “Grambihler”), in further view of Nettleton et al. (WO 2010124336 A1, hereinafter “Nettleton”) as applied to claim 1 above, in further view of Walker et al. (US 20210118066 A1, hereinafter “Walker”).
Regarding Claims 7: Humphrey doesn’t explicitly teach:
wherein: the processing plant data indicates that at least a first crusher, of the one or more crushers, will be unable to accept material during a period of time,
and the machine instructions adjust the first operations to divert one or more autonomous machines, in the fleet of autonomous machines, to autonomously deliver the loads of material to one or more other crushers different from the first crusher, or to at least one crusher of a different processing plant, during the period of time.
Walker further teaches:
wherein: the processing plant data indicates that at least a first crusher, of the one or more crushers, will be unable to accept material during a period of time, ([0080] If the crusher 16 is in neither the No-Material state nor the Closed state, then crusher 16 is deemed to be in an Accepting Material state.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times. These predictions, in conjunction with the estimated idle times predicted in step 54, may be used in step 60 to direct the movement of the haul trucks 18 to minimize the idle time and/or the time when the crusher 16 will be in the No-Material state. For example, the system and method of the present invention may tolerate a no-truck condition at the crusher 16 at some future time so long as the crusher is not predicted to be in the No-Material state before the predicted arrival of the next haul truck 18. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher 16 to enter the No-Material state before the predicted arrival of the next haul truck 18, then the director 38 may direct that the crusher 16 be fed instead from the crusher stockpile 60 (FIG. 1). Alternatively, the director 38 may direct (or redirect) one or more haul trucks 18 so that the predicted No-Material state can be avoided, or at least minimize the duration of the No-Material state. On the other hand, if too many haul trucks 18 are predicted to be at the crusher 16 at some future time, the director 38 may redirect one or more haul trucks 18 to other locations so as to minimize the idle time for haul trucks 18 at the crusher 16.);
and the machine instructions adjust the first operations to divert one or more autonomous machines, in the fleet of autonomous machines, to autonomously deliver the loads of material to one or more other crushers different from the first crusher, or to at least one crusher of a different processing plant, during the period of time. ([0043] the system 10 and method 44 may then direct the movement of the haul trucks 18 in order to minimize one or both of the haul truck idle time (i.e., at either or both of the ore crusher(s) 16 and loading area(s) 20) while ensuring that the ore crusher 16 never runs out of ore, i.e., enters the No-Material state. If necessary, the system 10 and method 44 may assign new destinations to the haul trucks 18, such as, for example, by assigning, directing, or redirecting one or more loaded haul trucks 18 to the crusher stockpile 60 or to another extraction process (not shown). In embodiments that involve the use of multiple ore crushers 16, the system 10 and method 44 of the present invention may assign, direct, or redirect one or more haul trucks 18 to an alternate ore crusher, thereby ensuring a steady delivery of ore to the various processing systems.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Walker’s additional features listed above. One would’ve been motivated to do so in order to determine when the ore crusher 16 will be “open for business” (Walker; [0045]). By incorporating the teachings of Walker, one would’ve been able to adjust operations when a crusher is unable to accept material.
Claims 10-12, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Humphrey (US 20160342915 A1, hereinafter “Humphrey”), in view of Grambihler et al. (US 20210325899 A1, hereinafter “Grambihler”).
Regarding Claims 10: Humphrey teaches a fleet management controller ([0003] a dispatching system for controlling the vehicles within a mine may be used to optimize material transport) with limitations for:
a processor; ([0021] The computing system 300 may comprise a processor 302);
and a memory having stored thereon computer-executable instructions that when executed by the processor cause the processor to: ([0021] The memory 308 may store instructions the processor 302 may execute to carry out one aspect of this disclosure);
generate machine instructions that dynamically control first operations of a fleet of autonomous machines, the first operations comprising the fleet of autonomous machines autonomously delivering loads of material to a processing plant, based at least in part on second operations of the processing plant indicated by processing plant data; ([0062] At 710, the processor 302 determines whether any of the autonomous vehicles 104 or the non-autonomous vehicles 106 may currently be bunching together or may bunch together in the future. Vehicle bunching indicates that there are too many vehicles 104 and 106 active within the work site 100. Therefore, the work site 100 is incurring extra costs by using extra vehicles 104 and 106 which do not increase the productivity of the work site 100. The processor 302 may determine that there is vehicle bunching by, for example, using the state, location, and travel information provided by the vehicles 104 and 106. For example, there may be more than one vehicle 104 or 106 waiting to service a shovel 108 or a processing site 110. The processor 302 may interpret this situation as evidence of vehicle bunching. If the processor 302 determines that there is vehicle bunching, the method may proceed to 714.; [0063] At 714, the processor 302 may transmit instructions to one of the autonomous vehicles 104 to discontinue serving the shovel 108 or processing site 110. If the autonomous vehicle 104 is not carrying material, the transmitted instructions may include instructions to follow a different route to a location where the autonomous vehicle 104 may become idle. Alternatively, if the autonomous vehicle 104 is transporting material, the transmitted instructions may include instructions to complete transporting the materials.; [0064] Returning to 710, if the processor 302 determines that there is no vehicle bunching, the method may proceed to 712.; [0065] At 712, since there are no available shovels 108 or processing sites 110 and there is no vehicle bunching, the processor 302 does not change the operation of the work site 100. For example, since there are no available shovels 108 or processing sites 110, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to activate and follow a route to an available shovel 108 or processing site 110, as explained above. Additionally, since there may be no vehicle bunching within the work site 100, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to become idle, as explained above.);
receive the processing plant data from a plant management controller, different from the fleet management controller, ([0003] a dispatching system for controlling the vehicles within a mine may be used to optimize material transport and reduce costs.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.; [0006] In another aspect, this disclosure describes a system for managing a fleet of vehicles, the system comprising a work site comprising a plurality of vehicles; a plurality of autonomous vehicles, each autonomous vehicle comprising an electronic processing unit configured to transmit data to a second location; a first location with an electronic processing unit configured to transmit data to the second location; and the second location with an electronic processing unit configured to determine, in response to the data transmitted by the plurality of autonomous vehicles and the first location, whether the first location is available to service a vehicle, the electronic processing unit of the second location is further configured to dispatch at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and to deactivate at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.);
wherein: the plant management controller is configured to dynamically control the second operations of the processing plant, the second operations comprising one or more crushers of the processing plant processing the loads of material delivered by the fleet of autonomous machines, based at least in part on material load data received from the fleet management controller, ([0002] This model has particular application in the mining industry, where material transportation involves a vehicle picking up a load of ore from a shovel site and transporting that ore to a processing site.; [0003] A processing site, broadly defined, encompasses any machine which may process mined ore or other materials delivered to it. For example, a processing site may include crusher machines; [0022] The computing system located at a shovel 108 also comprises a processor, one or more inputs, one or more outputs, a memory, and one or more transceivers. For example, if the shovel 108 is not operating in the manner it was designed to operate, the one or more outputs may display a user information or an alert that the shovel 108 is not operating in the manner it was designed to operate. For example, the shovel 108 may have become broken. The memory may comprise a computer readable memory to store instructions the processor may execute, according to one aspect of this disclosure. The instructions the processor may execute are further described herein.; [0023] The processing site 110 has a computing system similar to that of shovel 108 and it operates in a similar manner.; [0030] One way a processing site 110 may service a vehicle 104 or 106 is to unload the material the vehicle 104 or 106 may be transporting. The performance metrics may be instantaneous. For example, the shovel 108 may time how long it is taking to load the vehicle 104 or 106 it is currently servicing. Also, the processing site 110 may time how long it is taking to unload the vehicle 104 or 106 it is currently servicing. Alternatively, or additionally, to collecting instantaneous performance metrics is to store historical performance metrics. Once the shovel 108 or processing site 110 has collected the performance metrics, the method may proceed to step 506.);
adjust the machine instructions to dynamically change the first operations autonomously performed by the fleet of autonomous machines: in response to the second operations of the processing plant indicated by the processing plant data received from the plant management controller, ([0062] At 710, the processor 302 determines whether any of the autonomous vehicles 104 or the non-autonomous vehicles 106 may currently be bunching together or may bunch together in the future. Vehicle bunching indicates that there are too many vehicles 104 and 106 active within the work site 100. Therefore, the work site 100 is incurring extra costs by using extra vehicles 104 and 106 which do not increase the productivity of the work site 100. The processor 302 may determine that there is vehicle bunching by, for example, using the state, location, and travel information provided by the vehicles 104 and 106. For example, there may be more than one vehicle 104 or 106 waiting to service a shovel 108 or a processing site 110. The processor 302 may interpret this situation as evidence of vehicle bunching. If the processor 302 determines that there is vehicle bunching, the method may proceed to 714.; [0063] At 714, the processor 302 may transmit instructions to one of the autonomous vehicles 104 to discontinue serving the shovel 108 or processing site 110. If the autonomous vehicle 104 is not carrying material, the transmitted instructions may include instructions to follow a different route to a location where the autonomous vehicle 104 may become idle. Alternatively, if the autonomous vehicle 104 is transporting material, the transmitted instructions may include instructions to complete transporting the materials.; [0064] Returning to 710, if the processor 302 determines that there is no vehicle bunching, the method may proceed to 712.; [0065] At 712, since there are no available shovels 108 or processing sites 110 and there is no vehicle bunching, the processor 302 does not change the operation of the work site 100. For example, since there are no available shovels 108 or processing sites 110, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to activate and follow a route to an available shovel 108 or processing site 110, as explained above. Additionally, since there may be no vehicle bunching within the work site 100, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to become idle, as explained above.);
and to cause the fleet of autonomous machines to deliver particular loads of material, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0032] the shovel 108 loads vehicles 104 and 106 with material, such as mined ore.);
comprising material having particular attributes associated with the material blends indicated by the material target data, to the one or more crushers; ([0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste.; [0033] For example, the processing site 110 may perform work more slowly because, for example, the type of material it is unloading.; [0003] For example, a processing site may include crusher machines, waste storage sites, or ore storage sites.);
cause the fleet of autonomous machines to autonomously perform the first operations, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.).
dynamically changed in response to the second operations of the processing plant, by wirelessly sending the machine instructions to the fleet of autonomous machines; ([0026] Additionally, the autonomous vehicle 104 may be remotely activated using activate switch 412 after receiving an instruction to activate from the central site 102. For example, if the processor 302 at the central site 102 determines that an additional autonomous vehicle 104 would be beneficial, the processor 302 may transmit an instruction, via the one or more transceivers 310, to the autonomous vehicle 104 to activate. In addition to receiving instructions to activate, the autonomous vehicle 104 may also receive routing instructions. The routing instructions may instruct the autonomous vehicle 104 to travel along a given route to a shovel 108 or a processing site 110. Alternatively, if the autonomous vehicle 104 is active and serving a shovel 108 or a processing site 110, the autonomous vehicle 104 may receive instructions from the processor 302 located at the central site 102 to deactivate using the activate switch 412. The autonomous vehicle 104 may receive instructions to travel to a deactivated autonomous vehicle location. The autonomous vehicle 104 may also receive routing instructions from the central site 102 to direct the autonomous vehicle 104 from its current location to the deactivated autonomous vehicle location.).
Humphrey doesn’t explicitly teach:
and the processing plant data, indicative of the second operations of the processing plant, comprises material target data indicating material blends processed by the one or more crushers;
and provide the material load data to the plant management controller, wherein the material load data indicates respective contents of the particular loads of material to be delivered to the one or more crushers by the fleet of autonomous machines based on the machine instructions.
Grambihler teaches:
and the processing plant data, indicative of the second operations of the processing plant, comprises material target data indicating material blends processed by the one or more crushers; ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing.; [0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed.);
and provide the material load data to the plant management controller, wherein the material load data indicates respective contents of the particular loads of material to be delivered to the one or more crushers by the fleet of autonomous machines based on the machine instructions. ([0028] the worksite management computing device 106 determines the location for the hauling machine 102 to discharge the load based on the material data (e.g., type, composition, characteristics, etc.) associated with the load (e.g., material loaded in the hauling machine 102. In such examples, the worksite management computing device 106 accesses the worksite data 114 to determine the material data associated with material loaded into a hauling machine and determines a discharge location 130 based on the material data. For example, a worksite management computing device 106 determines, based on worksite data 114, that a hauling machine is loaded with leach material. Based on the determination that the load includes leach material, the worksite management computing device 106 determines a location associated with a leach field for the hauling machine 102 to discharge the load. For another example, a worksite management computing device 106 determines, based on worksite data 114, that a hauling machine is loaded with overburden material. Based on the determination that the load includes overburden material, the worksite management computing device 106 sends an instruction to the hauling machine computing device 120 for the hauling machine 102 to discharge the load at the overburden pile 112.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to send an instruction to a hauling machine computing device 120 associated with the hauling machine 102(c) (not illustrated) to deliver the ore to the crushing machine 104 (Grambihler; [0029]). By incorporating the teachings of Grambihler, one would’ve been able to use material data to understand the characteristics of the material that will be processed and deliver the material based, in part, on the material load data.
Regarding Claim 11: Humphrey doesn’t explicitly teach:
wherein the processing plant data comprises crusher operational data, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers, current bin fullness levels of the one or more crushers, threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers.
Grambihler teaches:
wherein the processing plant data comprises crusher operational data, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers, ([0131] historical data 936 and the historical data 938 include data associated with servicing (e.g., maintenance history) the crushing machine(s) 104 and the hauling machine(s) 102, respectively, and/or other data associated with the functioning of the crushing machine(s) 104 and the hauling machine(s) 102, respectively.); current bin fullness levels of the one or more crushers, ([Fig. 4] step 410: Receive, from a crusher computing device, sensor data associated with an amount of material in the crusher; [0021] the capacity of the discharge location may be determined, at least in part on sensor data associated with a receiving machine (e.g., crushing machine 104); [0032] the crushing machine computing device 122 sends the current capacity to the worksite management computing device 106 in real-time or near real-time); threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers. ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing. The worksite management computing device 106 receives second sensor data at a second time from the capacity sensor 118 and determines that, at the second time, a second amount of material in the crushing machine is above a second threshold amount.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to decrease the discharge rate of material from the hauling machine based on the second amount of material (Grambihler; [0026]). By incorporating the teachings of Grambihler, one would’ve been able to use crushing machine data to make decisions.
Regarding Claim 12: Humphrey doesn’t explicitly teach:
wherein the processing plant data comprises material processing rate data indicating one or more of: current material processing rates of the one or more crushers, or changes to material processing rates of the one or more crushers over a period of time.
Grambihler teaches:
wherein the processing plant data comprises material processing rate data indicating one or more of: current material processing rates of the one or more crushers, ([0031] a second crushing machine 104 is configured to process large rocks at a rate of approximately 10 tons per hour.); or changes to material processing rates of the one or more crushers over a period of time. ([0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed. In such examples, the amount of material that the crushing machine 404 can process over a time period (e.g., tons per hour) is based in part on a type, composition, and/or characteristic associated with the material. For example, a crushing machine 404 processes 10 tons of large rocks per hour and 20 tons of medium sized rocks per hour.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to optimize performance of the receiving machine 404 (Grambihler; [0078]). By incorporating the teachings of Grambihler, one would’ve been able to modify processing rates of material based on the capacity of the crushers.
Regarding Claim 14: Humphrey doesn’t explicitly teach:
wherein: the processing plant data indicates, to the fleet management controller, a decrease in a material processing rate of the one or more crushers over a period of time,
and the machine instructions adjust the first operations to reduce a material delivery rate, associated with the fleet of autonomous machines autonomously delivering the loads of material to the processing plant, to correspond with the decrease in the material processing rate.
Grambihler teaches:
wherein: the processing plant data indicates, to the fleet management controller, a decrease in a material processing rate of the one or more crushers over a period of time, ([0026] The worksite management computing device 106 continues to monitor an amount of material associated with the crushing machine 104 based on the sensor data, and continues to increase and/or decrease the discharge rate from the hauling machine 102 based on the sensor data until receiving an indication from the hauling machine 102 that a transfer of material is complete.);
and the machine instructions adjust the first operations to reduce a material delivery rate, associated with the fleet of autonomous machines autonomously delivering the loads of material to the processing plant, to correspond with the decrease in the material processing rate. ([0020] The hauling machine(s) 102 may be autonomous, semi-autonomous, or manually operated machines.; [0047] the hauling machine computing device 120 sends a command to the bed angle controller 134 to begin raising the bed to a threshold angle (e.g., 15 degrees, 20 degrees). The threshold angle includes an angle at which material will not be discharged from the bed of the hauling machine 102.; [0033] Based on the current capacity, the rate determination component 126 may determine that a slower discharge rate (e.g., 30 tons per hour less) will avoid overloading the crushing machine 104. One of ordinary skill in the art would reasonably interpret the commands to set the bed at a specific angle as equivalent to an adjustment to the material delivery operation based on the capacity of the receiving machine.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s additional features listed above. One would’ve been motivated to do so in order to determine the discharge rate for a current load (Grambihler; [0034]). By incorporating the teachings of Grambihler, one would’ve been able to adjust operations based on the current capacity of a crusher.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Humphrey (US 20160342915 A1, hereinafter “Humphrey”), in view of Grambihler et al. (US 20210325899 A1, hereinafter “Grambihler”), as applied to claim 10 above, in further view of Walker et al. (US 20210118066 A1, hereinafter “Walker”).
Regarding Claims 13: Humphrey doesn’t explicitly teach:
wherein: the processing plant data indicates that a first crusher, of the one or more crushers, will be unable to accept material during a period of time,
and the machine instructions are adjusted to divert one or more autonomous machines, in the fleet of autonomous machines, to autonomously deliver the loads of material to one or more other crushers different from the first crusher, or to at least one crusher of a different processing plant, during the period of time.
Walker further teaches:
wherein: the processing plant data indicates that a first crusher, of the one or more crushers, will be unable to accept material during a period of time, ([0080] If the crusher 16 is in neither the No-Material state nor the Closed state, then crusher 16 is deemed to be in an Accepting Material state.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times. These predictions, in conjunction with the estimated idle times predicted in step 54, may be used in step 60 to direct the movement of the haul trucks 18 to minimize the idle time and/or the time when the crusher 16 will be in the No-Material state. For example, the system and method of the present invention may tolerate a no-truck condition at the crusher 16 at some future time so long as the crusher is not predicted to be in the No-Material state before the predicted arrival of the next haul truck 18. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher 16 to enter the No-Material state before the predicted arrival of the next haul truck 18, then the director 38 may direct that the crusher 16 be fed instead from the crusher stockpile 60 (FIG. 1). Alternatively, the director 38 may direct (or redirect) one or more haul trucks 18 so that the predicted No-Material state can be avoided, or at least minimize the duration of the No-Material state. On the other hand, if too many haul trucks 18 are predicted to be at the crusher 16 at some future time, the director 38 may redirect one or more haul trucks 18 to other locations so as to minimize the idle time for haul trucks 18 at the crusher 16.);
and the machine instructions are adjusted to divert one or more autonomous machines, in the fleet of autonomous machines, to autonomously deliver the loads of material to one or more other crushers different from the first crusher, or to at least one crusher of a different processing plant, during the period of time. ([0043] the system 10 and method 44 may then direct the movement of the haul trucks 18 in order to minimize one or both of the haul truck idle time (i.e., at either or both of the ore crusher(s) 16 and loading area(s) 20) while ensuring that the ore crusher 16 never runs out of ore, i.e., enters the No-Material state. If necessary, the system 10 and method 44 may assign new destinations to the haul trucks 18, such as, for example, by assigning, directing, or redirecting one or more loaded haul trucks 18 to the crusher stockpile 60 or to another extraction process (not shown). In embodiments that involve the use of multiple ore crushers 16, the system 10 and method 44 of the present invention may assign, direct, or redirect one or more haul trucks 18 to an alternate ore crusher, thereby ensuring a steady delivery of ore to the various processing systems.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Walker’s additional features listed above. One would’ve been motivated to do so in order to determine when the ore crusher 16 will be “open for business” (Walker; [0045]). By incorporating the teachings of Walker, one would’ve been able to adjust operations when a crusher is unable to accept material.
Claims 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over Humphrey (US 20160342915 A1, hereinafter “Humphrey”), in view of Walker et al. (US 20210118066 A1, hereinafter “Walker”). in further view of Nettleton et al. (WO 2010124336 A1, hereinafter “Nettleton”), in further view of Grambihler et al. (US 20210325899 A1, hereinafter “Grambihler”),
Regarding Claim 15: Humphrey teaches a worksite system ([0001] This patent disclosure relates generally to managing an autonomous fleet of vehicles and, more particularly, to a system and method for increasing work site efficiency.) comprising:
a plurality of autonomous machines configured to autonomously perform first operations ([Abstract] A system for managing a fleet of vehicles, the system including a work site including a plurality of vehicles; a plurality of autonomous vehicles, each autonomous vehicle including an electronic processing unit configured to transmit data to a second location), the first operations comprising the plurality of autonomous machines: being loaded with loads of material at a worksite)[0040] the one or more inputs 404 may provide information relating to whether the autonomous vehicle 104 is loaded or empty and, if it is loaded, whether the autonomous vehicle 104 is loaded with mined material or with waste.), and autonomously delivering the loads of material to at least one processing plant; configured to process the loads of material via second operations, the second operations comprising one or more crushers of the at least one processing plant processing the loads of material delivered by the plurality of autonomous machines; ([0003] a mining site may have multiple shovels and multiple processing sites. A shovel, broadly defined, encompasses any piece of equipment that delivers a load to a vehicle. For example, shovels may include a bulldozer, a dragline, track loaders, wheel loaders, a motor grader, a mass excavator, a scraper, an electric shovel, a hydraulic shovel, a continuous miner, a scaler, or a scooptram. A processing site, broadly defined, encompasses any machine which may process mined ore or other materials delivered to it.; [Abstract] A system for managing a fleet of vehicles, the system including a work site including a plurality of vehicles; a plurality of autonomous vehicles, each autonomous vehicle including an electronic processing unit configured to transmit data to a second location; a first location with an electronic processing unit configured to transmit data to the second location; and the second location with an electronic processing unit configured to determine, in response to the data transmitted by the plurality of autonomous vehicles and the first location, whether the first location is available to service a vehicle, the electronic processing unit of the second location is further configured to dispatch at least one autonomous vehicle to the first location if the first location in the work site is underserved by vehicles, and to deactivate at least one autonomous vehicle serving the first location if the first location in the work site is overserved by vehicles is disclosed.);
a fleet management controller, executed via a first computing system, configured to dynamically manage the first operations, autonomously performed by the plurality of autonomous machines at the worksite, based at least in part on the second operations of the at least one processing plant indicated by processing plant data; ([0062] At 710, the processor 302 determines whether any of the autonomous vehicles 104 or the non-autonomous vehicles 106 may currently be bunching together or may bunch together in the future. Vehicle bunching indicates that there are too many vehicles 104 and 106 active within the work site 100. Therefore, the work site 100 is incurring extra costs by using extra vehicles 104 and 106 which do not increase the productivity of the work site 100. The processor 302 may determine that there is vehicle bunching by, for example, using the state, location, and travel information provided by the vehicles 104 and 106. For example, there may be more than one vehicle 104 or 106 waiting to service a shovel 108 or a processing site 110. The processor 302 may interpret this situation as evidence of vehicle bunching. If the processor 302 determines that there is vehicle bunching, the method may proceed to 714.; [0063] At 714, the processor 302 may transmit instructions to one of the autonomous vehicles 104 to discontinue serving the shovel 108 or processing site 110. If the autonomous vehicle 104 is not carrying material, the transmitted instructions may include instructions to follow a different route to a location where the autonomous vehicle 104 may become idle. Alternatively, if the autonomous vehicle 104 is transporting material, the transmitted instructions may include instructions to complete transporting the materials.; [0064] Returning to 710, if the processor 302 determines that there is no vehicle bunching, the method may proceed to 712.; [0065] At 712, since there are no available shovels 108 or processing sites 110 and there is no vehicle bunching, the processor 302 does not change the operation of the work site 100. For example, since there are no available shovels 108 or processing sites 110, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to activate and follow a route to an available shovel 108 or processing site 110, as explained above. Additionally, since there may be no vehicle bunching within the work site 100, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to become idle, as explained above.);
and a plant management controller, executed via a second computing system, configured to dynamically manage the second operations of the at least one processing plant based at least in part on material load data received from the fleet management controller, ([0002] This model has particular application in the mining industry, where material transportation involves a vehicle picking up a load of ore from a shovel site and transporting that ore to a processing site.; [0003] A processing site, broadly defined, encompasses any machine which may process mined ore or other materials delivered to it. For example, a processing site may include crusher machines; [0022] The computing system located at a shovel 108 also comprises a processor, one or more inputs, one or more outputs, a memory, and one or more transceivers. For example, if the shovel 108 is not operating in the manner it was designed to operate, the one or more outputs may display a user information or an alert that the shovel 108 is not operating in the manner it was designed to operate. For example, the shovel 108 may have become broken. The memory may comprise a computer readable memory to store instructions the processor may execute, according to one aspect of this disclosure. The instructions the processor may execute are further described herein.; [0023] The processing site 110 has a computing system similar to that of shovel 108 and it operates in a similar manner.; [0030] One way a processing site 110 may service a vehicle 104 or 106 is to unload the material the vehicle 104 or 106 may be transporting. The performance metrics may be instantaneous. For example, the shovel 108 may time how long it is taking to load the vehicle 104 or 106 it is currently servicing. Also, the processing site 110 may time how long it is taking to unload the vehicle 104 or 106 it is currently servicing. Alternatively, or additionally, to collecting instantaneous performance metrics is to store historical performance metrics. Once the shovel 108 or processing site 110 has collected the performance metrics, the method may proceed to step 506.);
wherein the fleet management controller: receives the processing plant data from the plant management controller, the processing plant data indicating the second operations ([0003] a dispatching system for controlling the vehicles within a mine may be used to optimize material transport and reduce costs.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.; [0006] In another aspect, this disclosure describes a system for managing a fleet of vehicles, the system comprising a work site comprising a plurality of vehicles; a plurality of autonomous vehicles, each autonomous vehicle comprising an electronic processing unit configured to transmit data to a second location; a first location with an electronic processing unit configured to transmit data to the second location; and the second location with an electronic processing unit configured to determine, in response to the data transmitted by the plurality of autonomous vehicles and the first location, whether the first location is available to service a vehicle, the electronic processing unit of the second location is further configured to dispatch at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and to deactivate at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.);
generates machine instructions that dynamically adjust the first operations of the plurality of autonomous machines in response to the second operations of the at least one processing plant indicated by the processing plant data received from the plant management controller, ([0062] At 710, the processor 302 determines whether any of the autonomous vehicles 104 or the non-autonomous vehicles 106 may currently be bunching together or may bunch together in the future. Vehicle bunching indicates that there are too many vehicles 104 and 106 active within the work site 100. Therefore, the work site 100 is incurring extra costs by using extra vehicles 104 and 106 which do not increase the productivity of the work site 100. The processor 302 may determine that there is vehicle bunching by, for example, using the state, location, and travel information provided by the vehicles 104 and 106. For example, there may be more than one vehicle 104 or 106 waiting to service a shovel 108 or a processing site 110. The processor 302 may interpret this situation as evidence of vehicle bunching. If the processor 302 determines that there is vehicle bunching, the method may proceed to 714.; [0063] At 714, the processor 302 may transmit instructions to one of the autonomous vehicles 104 to discontinue serving the shovel 108 or processing site 110. If the autonomous vehicle 104 is not carrying material, the transmitted instructions may include instructions to follow a different route to a location where the autonomous vehicle 104 may become idle. Alternatively, if the autonomous vehicle 104 is transporting material, the transmitted instructions may include instructions to complete transporting the materials.; [0064] Returning to 710, if the processor 302 determines that there is no vehicle bunching, the method may proceed to 712.; [0065] At 712, since there are no available shovels 108 or processing sites 110 and there is no vehicle bunching, the processor 302 does not change the operation of the work site 100. For example, since there are no available shovels 108 or processing sites 110, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to activate and follow a route to an available shovel 108 or processing site 110, as explained above. Additionally, since there may be no vehicle bunching within the work site 100, the processor 302 may not need to generate and transmit instructions to an autonomous vehicle 104 to become idle, as explained above.);
and to cause the fleet of autonomous machines to deliver particular loads of material, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0032] the shovel 108 loads vehicles 104 and 106 with material, such as mined ore.);
comprising material having particular attributes associated with the material blends indicated by the material target data, to the one or more crushers; ([0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste.; [0033] For example, the processing site 110 may perform work more slowly because, for example, the type of material it is unloading.; [0003] For example, a processing site may include crusher machines, waste storage sites, or ore storage sites.);
causes the plurality of autonomous machines to autonomously perform the first operations, ([0015] Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.; [0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.).
dynamically adjusted in response to the second operations of the at least one processing plant, by wirelessly sending the machine instructions to the plurality of autonomous machines; ([0026] Additionally, the autonomous vehicle 104 may be remotely activated using activate switch 412 after receiving an instruction to activate from the central site 102. For example, if the processor 302 at the central site 102 determines that an additional autonomous vehicle 104 would be beneficial, the processor 302 may transmit an instruction, via the one or more transceivers 310, to the autonomous vehicle 104 to activate. In addition to receiving instructions to activate, the autonomous vehicle 104 may also receive routing instructions. The routing instructions may instruct the autonomous vehicle 104 to travel along a given route to a shovel 108 or a processing site 110. Alternatively, if the autonomous vehicle 104 is active and serving a shovel 108 or a processing site 110, the autonomous vehicle 104 may receive instructions from the processor 302 located at the central site 102 to deactivate using the activate switch 412. The autonomous vehicle 104 may receive instructions to travel to a deactivated autonomous vehicle location. The autonomous vehicle 104 may also receive routing instructions from the central site 102 to direct the autonomous vehicle 104 from its current location to the deactivated autonomous vehicle location.).
and provides the material load data to the plant management controller, the material load data indicating respective contents of the particular loads of material to be delivered to the one or more crushers by the plurality of autonomous machines based on the machine instructions, ([0025] The autonomous vehicle 104 may transmit information about a state, location, travel, and health information regarding the autonomous vehicle 104. Information about the state of the autonomous vehicle 104 may include whether the autonomous vehicle 104 is loaded or empty. It may also include what type of load it is carrying, for example, ore or waste. Any appropriate sensor coupled to the autonomous vehicle 104 may be used to generate a signal indicative of the state of the autonomous vehicle 104. Information about the location of the autonomous vehicle 104 may be based on a location sensor, such as a global navigation satellite system (GNSS) sensor. Travel information regarding the autonomous vehicle 104 may be gathered using various sensors coupled to the autonomous vehicle 104. For example, the autonomous vehicle 104 may gather information about its speed using a speedometer. Alternatively, the autonomous vehicle 104 may generate information about its speed using successive GNSS signal measurements. The autonomous vehicle 104 may also transmit its direction of travel using successive GNSS signals. The processor 402 may generate the direction of travel based on a line formed by two successive GNSS signals. Alternatively, instead of the autonomous vehicle 104 generating the direction of travel, the processor 302 at the central site 102 may generate the direction of travel based on the successive GNSS signals received from the autonomous vehicle 104.; [0026] Additionally, the autonomous vehicle 104 may be remotely activated using activate switch 412 after receiving an instruction to activate from the central site 102. For example, if the processor 302 at the central site 102 determines that an additional autonomous vehicle 104 would be beneficial, the processor 302 may transmit an instruction, via the one or more transceivers 310, to the autonomous vehicle 104 to activate. In addition to receiving instructions to activate, the autonomous vehicle 104 may also receive routing instructions. The routing instructions may instruct the autonomous vehicle 104 to travel along a given route to a shovel 108 or a processing site 110. Alternatively, if the autonomous vehicle 104 is active and serving a shovel 108 or a processing site 110, the autonomous vehicle 104 may receive instructions from the processor 302 located at the central site 102 to deactivate using the activate switch 412. The autonomous vehicle 104 may receive instructions to travel to a deactivated autonomous vehicle location. The autonomous vehicle 104 may also receive routing instructions from the central site 102 to direct the autonomous vehicle 104 from its current location to the deactivated autonomous vehicle location.);
and wherein the plant management controller: provides the processing plant second data to the fleet management controller; ([0005] In one aspect, this disclosure describes a method for managing a fleet of vehicles, the method comprising: receiving data regarding a work site at an electronic processing unit at a first location, wherein the work site comprises a plurality of vehicles; and determining, at the electronic processing unit and in response to the received data, whether a second location in the work site is available to service a vehicle, dispatching, via the electronic processing unit, at least one autonomous vehicle to the second location if the second location in the work site is underserved by vehicles, and deactivating, via the electronic processing unit, at least one autonomous vehicle serving the second location if the second location in the work site is overserved by vehicles.; [0014] Reference will now be made in detail to aspects of this disclosure, examples of which are illustrated in the accompanying drawings. Wherever possible, the same reference numbers will be used throughout the drawings to refer to the same or like parts throughout. Additionally, a work site may have a plurality of autonomous vehicles, a plurality of non-autonomous vehicles, a plurality of shovels, and a plurality of processing sites. While this disclosure will describe aspects of a system and a method with one autonomous vehicle, one non-autonomous vehicle, one shovel, and one processing site, this disclosure should not be understood to be limited to such.; [0015] In general, and in reference to FIGS. 1-3, this disclosure comprises a central site 102 in a work site 100, such as a mine, with a computing system 300. The work site 100 comprises a plurality of shovels 108 and a plurality of processing sites 110, such as crushers. Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110. However, during normal operation of the work site 100, there may be variations in vehicle cycle time from a shovel 108 to a processing site 110 and back to the shovel 108. For example, a shovel 108 or a processing site 110 may fail to operate correctly or load or unload a vehicle 104 and 106 more slowly than anticipated, which may delay vehicles 104 and 106. Additionally, there may be variations caused by in route congestion. In route congestion may be caused, for example, by a failed vehicle traversing a route. If a vehicle fails along its route, it may delay vehicles behind it from reaching their destination on time. These variations may result in vehicles 104 and 106 “bunching” in one area of the work site 100. This bunching may result in one or more shovels 108 or processing sites 110 being underserved by trucks 104 and 106. Thus, the efficiency of the shovel 108, and the work site 100 as a whole, is reduced. To prevent the work site 100 from operating in a less efficient manner, the computing system 300 located at the central site 102 in the work site 100 may determine that a shovel 108 or processing site 110 is underserved on a moment by moment basis. To prevent the shovel 108 or processing site 110 from being underserved, the computing system 300 at the central site 102 may deploy one or more autonomous vehicles 104 to the underserved shovel 108 or processing site 110. Alternatively, if the computing system 300 determines that there are too many vehicles 104 and 106 within the work site 100, the computing system 300 may remove one or more autonomous vehicles 104 from the work site 100.);
receives the material load first data from the fleet management controller; ([0058] The processor 302 may use the state information provided by the autonomous vehicles 104 and the non-autonomous vehicles 106 to determine the availability of the autonomous vehicles 104. For example, if the autonomous vehicle 104 transmits data indicating that it is empty, then the processor 302 may use this data to determine that the autonomous vehicle 104 is available to be used. Alternatively, if the autonomous vehicle 104 transmits data indicating that it is carrying material, for example, ore or waste, then the processor 302 may determine that the autonomous vehicle 104 is not available to be used.);
Humphrey doesn’t explicitly teach:
a fleet management controller, executed via a first computing system
and a plant management controller, executed via a second computing system
and comprising material target data indicating material blends processed by the one or more crushers;
generates plant instructions that dynamically adjust the second operations of the at least one processing plant in response to the first operations of the plurality of autonomous machines indicated by the material load data received from the fleet management controller;
and causes one or more elements of the at least one processing plant to perform the second operations, dynamically adjusted in response to the first operations of the plurality of autonomous machines, by sending the plant instructions to the one or more elements of the at least one processing plant.
Walker teaches:
generates plant instructions that dynamically adjust the second operations of the at least one processing plant in response to the first operations of the plurality of autonomous machines indicated by the material load data received from the fleet management controller; ([0084] The High limit 88 represents that level 61 of crushed ore 62 above which the crusher control system (not shown) will shut-down the crusher 16 to avoid floating the mantle. In one embodiment, the High limit 88 is selected to be about 80% of the surge bin capacity.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times.; [0015] FIG. 6 is a pictorial diagram including a tabular listing of predicted material splits for unloaded haul trucks; [0016] FIG. 7 is a pictorial diagram including a tabular listing of estimated times of arrival for trucks traveling too and from the ore crusher; [0017] FIG. 8 is a pictorial representation of a prediction window showing a prediction of the number of haul trucks predicted to be at the ore crusher at various future times);
and causes one or more elements of the at least one processing plant to perform the second operations, dynamically adjusted in response to the first operations of the plurality of autonomous machines, by sending the plant instructions to the one or more elements of the at least one processing plant. ([0083] The Operating limit 86 represents that level 61 of crushed ore 62 that will allow the surge bin 58 to accommodate crushed ore 62 produced by crusher 16 from the load carried by a single haul truck 18. That is, if the entire load of a single haul truck 18 is dumped into feed bin 26 (FIG. 1) of crusher 16 when the level 61 of crushed material 62 is at or below the Operating limit 86, the surge bin 58 will be able to accept the crushed ore 62 resulting from the entire load without exceeding the High limit 88. The Operating limit 86 is therefore related to the crush out time, the discharge rate of the surge bin 58, and the capacity of the haul truck 18. In one embodiment, the Operating limit 86 is selected to be about 60% of the surge bin capacity.; [0084] The High limit 88 represents that level 61 of crushed ore 62 above which the crusher control system (not shown) will shut-down the crusher 16 to avoid floating the mantle. In one embodiment, the High limit 88 is selected to be about 80% of the surge bin capacity.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times. These predictions, in conjunction with the estimated idle times predicted in step 54, may be used in step 60 to direct the movement of the haul trucks 18 to minimize the idle time and/or the time when the crusher 16 will be in the No-Material state. For example, the system and method of the present invention may tolerate a no-truck condition at the crusher 16 at some future time so long as the crusher is not predicted to be in the No-Material state before the predicted arrival of the next haul truck 18. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher 16 to enter the No-Material state before the predicted arrival of the next haul truck 18, then the director 38 may direct that the crusher 16 be fed instead from the crusher stockpile 60 (FIG. 1). Alternatively, the director 38 may direct (or redirect) one or more haul trucks 18 so that the predicted No-Material state can be avoided, or at least minimize the duration of the No-Material state. On the other hand, if too many haul trucks 18 are predicted to be at the crusher 16 at some future time, the director 38 may redirect one or more haul trucks 18 to other locations so as to minimize the idle time for haul trucks 18 at the crusher 16.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine Humphrey with Walker’s features listed above. One would’ve been motivated to do so in order to improve overall production efficiency by analyzing and controlling the operation of the system as a whole, i.e., shovel(s) 22, haul trucks 18, and ore crusher(s) 16 (Walker; [0042]). By incorporating the teachings of Walker, one would’ve been able to crush material, move crushed material and adjust operations based on data from other operations.
Walker doesn’t teach:
a fleet management controller, executed via a first computing system
and a plant management controller, executed via a second computing system
and comprising material target data indicating material blends processed by the one or more crushers;
Nettleton teaches:
a fleet management controller, executed via a first computing system ([Abstract] The autonomous entity is instructed to move into a transition zone (906, 907) that spans the first zone and the second zone, wherein the autonomous entity while located in the first zone is responsive to supervisory control of a first controller (912) associated with the first zone. The autonomous entity is registered with a second controller (910) associated with the second zone to enable the autonomous entity to respond to supervisory control of the second controller as the autonomous entity enters the second zone through the transition zone.; [Column 1, Lines 6-7] The invention has various applications and, in one of its possible embodiments, has application to a mine automation system; [Column 1, Lines 14-27] One example of a complex application where autonomous operations may be used is in mining. Conventional open pit mining, for example of metal-bearing mineral or rock, normally involves the progressive accessing of an ore body followed by drilling, blasting, loading and haulage of the released material. In the case of iron ore it is mined in large blocks from a series of benches and the various mining activities (other than blasting) are performed concurrently, resulting in diverse equipment, and often personnel, being present simultaneously in the mine site. A bench of ore typically 40m long x 20m deep χ10m high and containing in the order of 8 kilotonnes of ore is first drilled to form a pattern of blast holes and the drilling residue is analysed, as one step in a more extensive analysis, to determine whether the material to be blasted comprises, on average, high grade ore, low grade ore or waste material. The blasted material is collected by shovels, excavators and/or front end haul loaders, loaded into haul trucks and transported from the mine pit.);
and a plant management controller, executed via a second computing system ([Abstract] The autonomous entity is instructed to move into a transition zone (906, 907) that spans the first zone and the second zone, wherein the autonomous entity while located in the first zone is responsive to supervisory control of a first controller (912) associated with the first zone. The autonomous entity is registered with a second controller (910) associated with the second zone to enable the autonomous entity to respond to supervisory control of the second controller as the autonomous entity enters the second zone through the transition zone.; [Column 1, Lines 6-7] The invention has various applications and, in one of its possible embodiments, has application to a mine automation system; [Column 1, Lines 14-27] One example of a complex application where autonomous operations may be used is in mining. Conventional open pit mining, for example of metal-bearing mineral or rock, normally involves the progressive accessing of an ore body followed by drilling, blasting, loading and haulage of the released material. In the case of iron ore it is mined in large blocks from a series of benches and the various mining activities (other than blasting) are performed concurrently, resulting in diverse equipment, and often personnel, being present simultaneously in the mine site. A bench of ore typically 40m long x 20m deep χ10m high and containing in the order of 8 kilotonnes of ore is first drilled to form a pattern of blast holes and the drilling residue is analysed, as one step in a more extensive analysis, to determine whether the material to be blasted comprises, on average, high grade ore, low grade ore or waste material. The blasted material is collected by shovels, excavators and/or front end haul loaders, loaded into haul trucks and transported from the mine pit.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Nettleton’s features listed above. One would’ve been motivated to do so, so the material is then processed outside of the mine pit, depending upon grade determination (Nettleton; [Column 1, Lines 27-28]). By incorporating the teachings of Nettleton, one would’ve been able to use separate controllers, executed via different computing systems, to control the different operations.
Nettleton doesn’t explicitly teach:
and comprising material target data indicating material blends processed by the one or more crushers;
Grambihler teaches:
and comprising material target data indicating material blends processed by the one or more crushers; ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing.; [0077] the capability of the crushing machine 404 is determined based on material data (e.g., a type, composition, and/or characteristics) associated with the material to be processed.);
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s features listed above. One would’ve been motivated to do so in order to send an instruction to a hauling machine computing device 120 associated with the hauling machine 102(c) (not illustrated) to deliver the ore to the crushing machine 104 (Grambihler; [0029]). By incorporating the teachings of Grambihler, one would’ve been able to use material data to understand the characteristics of the material that will be processed and deliver the material based, in part, on the material load data.
Regarding Claim 16: Humphrey doesn’t teach:
wherein: the plant management controller generates the plant instructions, based on the material load data, to dynamically adjust the second operations of the at least one processing plant in anticipation of delivery of the particular loads of material to the one or more crushers.
Walker teaches:
wherein: the plant management controller generates the plant instructions, based on the material load data, to dynamically adjust the second operations of the at least one processing plant in anticipation of delivery of the particular loads of material to the one or more crushers. ([0084] The High limit 88 represents that level 61 of crushed ore 62 above which the crusher control system (not shown) will shut-down the crusher 16 to avoid floating the mantle. In one embodiment, the High limit 88 is selected to be about 80% of the surge bin capacity.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times.; [0015] FIG. 6 is a pictorial diagram including a tabular listing of predicted material splits for unloaded haul trucks; [0016] FIG. 7 is a pictorial diagram including a tabular listing of estimated times of arrival for trucks traveling too and from the ore crusher; [0017] FIG. 8 is a pictorial representation of a prediction window showing a prediction of the number of haul trucks predicted to be at the ore crusher at various future times);
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Walker’s features listed above. One would’ve been motivated to do so in order to improve overall production efficiency by analyzing and controlling the operation of the system as a whole, i.e., shovel(s) 22, haul trucks 18, and ore crusher(s) 16 (Walker; [0042]). By incorporating the teachings of Walker, one would’ve been able to crush material, move crushed material and adjust operations based on data from other operations.
Regarding Claim 17: Humphrey teaches
wherein the material load data indicates one or more of: material amounts in the particular loads of material, at least one material type associated with the particular loads of material ([0025] It may also include what type of load it is carrying, for example, ore or waste.), at least one material grade associated with the particular loads of material, at least one material size associated with the particular loads of material, identifiers of the one or more crushers, to which the particular loads of material are to be delivered, or at least one arrival time of the particular loads of material to the one or more crushers.
Regarding Claim 18: Humphrey doesn’t teach:
wherein the processing plant data comprises crusher operational data, associated with the one or more crushers, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers, current bin fullness levels of the one or more crushers, threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers.
Grambihler further teaches:
wherein the processing plant data comprises crusher operational data, associated with the one or more crushers, indicating one or more of: current statuses of the one or more crushers, planned maintenance times associated with the one or more crushers,
current bin fullness levels of the one or more crushers (Fig. 4, step 410: Receive, from a crusher computing device, sensor data associated with an amount of material in the crusher; [0021] the capacity of the discharge location may be determined, at least in part on sensor data associated with a receiving machine (e.g., crushing machine 104); [0032] the crushing machine computing device 122 sends the current capacity to the worksite management computing device 106 in real-time or near real-time), threshold fullness levels corresponding to closed indicators associated with the one or more crushers, or operational statuses of rock breakers associated with the one or more crushers. ([0026] the worksite management computing device 106 receives first sensor data at a first time from a capacity sensor 118 associated with the crushing machine 104 and determines that, at the first time, a first amount of material in the crushing machine 104 is below a first threshold amount (e.g., low capacity) and that the crushing machine 104 is ready to receive additional material for processing. The worksite management computing device 106 receives second sensor data at a second time from the capacity sensor 118 and determines that, at the second time, a second amount of material in the crushing machine is above a second threshold amount.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Grambihler’s additional features listed above. One would’ve been motivated to do so in order to decrease the discharge rate of material from the hauling machine based on the second amount of material (Grambihler; [0026]). By incorporating the teachings of Grambihler, one would’ve been able to use crushing machine data to make decisions.
Regarding Claim 19: Humphrey doesn’t teach:
wherein: the processing plant data indicates that a first crusher, of the one or more crushers, will be unable to accept material during a period of time,
and the fleet management controller generates the machine instructions to divert one or more autonomous machines, in the plurality of autonomous machines, to autonomously deliver the material to one or more other crushers different from the first crusher, during the period of time.
Walker teaches:
wherein: the processing plant data indicates that a first crusher, of the one or more crushers, will be unable to accept material during a period of time, ([0080] If the crusher 16 is in neither the No-Material state nor the Closed state, then crusher 16 is deemed to be in an Accepting Material state.; [0085] As mentioned, step 56 predicts the state of the crusher 16 at one or more future times based on the predicted number of haul trucks 18 at the crusher 16 as well as the level 61 of the crushed material 62 predicted to be in the surge bin 58 at the future times. These predictions, in conjunction with the estimated idle times predicted in step 54, may be used in step 60 to direct the movement of the haul trucks 18 to minimize the idle time and/or the time when the crusher 16 will be in the No-Material state. For example, the system and method of the present invention may tolerate a no-truck condition at the crusher 16 at some future time so long as the crusher is not predicted to be in the No-Material state before the predicted arrival of the next haul truck 18. However, if the no-truck condition will extend for a period of time sufficient to also allow the crusher 16 to enter the No-Material state before the predicted arrival of the next haul truck 18, then the director 38 may direct that the crusher 16 be fed instead from the crusher stockpile 60 (FIG. 1). Alternatively, the director 38 may direct (or redirect) one or more haul trucks 18 so that the predicted No-Material state can be avoided, or at least minimize the duration of the No-Material state. On the other hand, if too many haul trucks 18 are predicted to be at the crusher 16 at some future time, the director 38 may redirect one or more haul trucks 18 to other locations so as to minimize the idle time for haul trucks 18 at the crusher 16.);
and the fleet management controller generates the machine instructions to divert one or more autonomous machines, in the plurality of autonomous machines, to autonomously deliver the material to one or more other crushers different from the first crusher, during the period of time. ([0043] the system 10 and method 44 may then direct the movement of the haul trucks 18 in order to minimize one or both of the haul truck idle time (i.e., at either or both of the ore crusher(s) 16 and loading area(s) 20) while ensuring that the ore crusher 16 never runs out of ore, i.e., enters the No-Material state. If necessary, the system 10 and method 44 may assign new destinations to the haul trucks 18, such as, for example, by assigning, directing, or redirecting one or more loaded haul trucks 18 to the crusher stockpile 60 or to another extraction process (not shown). In embodiments that involve the use of multiple ore crushers 16, the system 10 and method 44 of the present invention may assign, direct, or redirect one or more haul trucks 18 to an alternate ore crusher, thereby ensuring a steady delivery of ore to the various processing systems.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine modified Humphrey with Walker’s additional features listed above. One would’ve been motivated to do so in order to determine when the ore crusher 16 will be “open for business” (Walker; [0045]). By incorporating the teachings of Walker, one would’ve been able to adjust operations when a crusher is unable to accept material.
Regarding Claim 20: Humphrey teaches:
associated with the plurality of autonomous machines autonomously delivering the material to the at least one processing plant, ([0015] The work site 100 comprises a plurality of shovels 108 and a plurality of processing sites 110, such as crushers. Vehicles, both autonomous and non-autonomous, transport material from the plurality of shovels 108 to the plurality of processing sites 110.).
Humphrey doesn’t teach:
wherein: the processing plant data indicates a decrease in a material processing rate of the one or more crushers over a period of time,
and the fleet management controller generates the machine instructions to reduce a material delivery rate, associated with the plurality of autonomous machines autonomously delivering the material to the at least one processing plant, to correspond with the decrease in the material processing rate.
Grambihler further teaches:
wherein: the processing plant data indicates a decrease in a material processing rate of the one or more crushers over a period of time, ([0026] The worksite management computing device 106 continues to monitor an amount of material associated with the crushing machine 104 based on the sensor data, and continues to increase and/or decrease the discharge rate from the hauling machine 102 based on the sensor data until receiving an indication from the hauling machine 102 that a transfer of material is complete.);
and the fleet management controller generates the machine instructions to reduce a material delivery rate, … …to correspond with the decrease in the material processing rate. ([0047] the hauling machine computing device 120 sends a command to the bed angle controller 134 to begin raising the bed to a threshold angle (e.g., 15 degrees, 20 degrees). The threshold angle includes an angle at which material will not be discharged from the bed of the hauling machine 102.; [0033] Based on the current capacity, the rate determination component 126 may determine that a slower discharge rate (e.g., 30 tons per hour less) will avoid overloading the crushing machine 104. One of skill in the art would reasonably interpret the commands to set the bed at a specific angle as an adjustment to the material delivery operation based on the capacity of the crushing machine.).
It would have been obvious to one of ordinary skill in the art, at the time of applicant’s invention, to combine Wei, Walker and Grambihler with Grambihler’s additional features listed above. One would’ve been motivated to do so in order to determine the discharge rate for a current load (Grambihler; [0034]). By incorporating the teachings of Grambihler, one would’ve been able to adjust operations based on the current capacity of a crusher.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/G.J.T./Examiner, Art Unit 3625
/SARA GRACE BROWN/Primary Examiner, Art Unit 3625
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