DETAILED ACTION
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Status
Claims 1, 8, 13-14, 17, 21, 26, and 47-51 and 53-54 are pending in this application. Claims 1, 26, 47, and 49 were amended. Claims 2, 11-12, and 52 were canceled.
Response to Arguments
Applicant’s arguments, see arguments/remarks, filed April 15, 2026, with respect to the rejection of claims 49-54 under 35 U.S.C. 101 on the grounds of encompassing a human organism, have been fully considered and are persuasive. These rejections of claims 49-54 have been withdrawn. Applicant has redacted language in claim 49 that formerly disclosed humans as part of a system invention. However, other rejections under 35 U.S.C. 101 continue to apply to claims 49-54; see response immediately below and also the rejections section later in this office action.
Applicant's arguments filed April 15, 2026, with respect to the rejection of all claims under 35 U.S.C. 101 on the grounds of the judicial exception for an abstract idea have been fully considered but they are not persuasive. While applicant has provided new limitations which disclose more details regarding its warehousing method, these details do not offer “significantly more” than the judicial exception for an abstract idea in the form of mental process and human organization.
We provide a revised detailed analysis in the rejections section below, but in response to applicant’s argument that its invention is a “concrete technical system, not an abstract idea” we present a briefly summarized response. We first remind applicant that unclaimed aspects of the instant specification do not factor into our analysis; we consider the claims first and use the specification to illuminate the meaning of the claims.
In considering exemplar claim 1, we find the following physical entities:
one or more warehouses. These warehouses provide nothing more than situational context for the invention as no structural features of the warehouses are claimed.
a controller. A controller or PLC is assumed to be a general-purpose computer in the absence of further structural limitations. The use of a computer does not add “significantly more” unless the state of computer art is advanced by the invention, which does not appear to be the case.
a centralized computer system. Ibid.
autonomous and human-controlled robots. These machines could well add “significantly more” to the invention if they were claimed to be more than mere black boxes devoid of structure and if they themselves advanced some industrial or commercial art. However, no such claim has been made. Thus we do not consider that the claimed robots add significantly more.
In the context of these broadly limited structures, applicant claims a method for communicating with and scheduling tasks for robots and humans. As noted in the previous action, this method combines two court-acknowledged forms of abstraction, namely mental process and methods of human organization. The amended claims, while now narrower and more detailed, still only claim these two combined categories of abstract idea, apart from the “insignificant extra-solution activity” of the above structures and devices.
For applicant’s method to provide “significantly more”, some system elements that are not well-understood, routine, and conventional, or some method steps not involving mental process or abstract communication would have to be claimed, and as yet no such claims have been advanced.
Applicant’s arguments with respect to the rejection of all claims under 35 U.S.C. 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
We concur with applicant’s argument that former primary reference Kattepur teaches away from the amended independent claims due to its preference for distributed control over centralized control. Applicant’s amendments triggered new search, however. We now cite primary reference Mason for centralized control and many other aspects of the independent claims, and relegate Kattepur as a secondary reference for selected teachings to be combined under Mason’s centralized control approach, adding new secondary reference Sarkar for further teaching of the independent claims.
Examiner’s Note
The examiner would welcome an interview to clarify any of the various rejections seen below in order to expedite prosecution of the instant application.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 8, 13-14, 17, 21, 26, 47-51 and 53-54 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 47, and 49 as amended recite the term “progressive velocity”. This nonstandard term does not appear in the instant specification, but the specification’s “progress velocity” ([0007] and [0089]) is close enough to the term of the claims not to require an objection on that ground. However, “progress velocity” is also nonstandard and not formally defined. To the limited extent it appears in external art, it appears to be a term in agile management that has no bearing on the physical properties of a robot or a human worker. We speculate that in context “progress velocity” may mean “maximum travel speed”, “average travel speed” or possibly “task completion rate”, but not only cannot we be certain which interpretation is preferred, this guesswork is not certain enough to render the claim definite. All dependent claims inherit the indefiniteness of claims 1, 47, and 49. For purposes of examination on the merits in this office action, we take “progress velocity” to mean either “maximum travel speed”, “average travel speed”, or “task completion rate”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 8, 13-14, 17, 21, 26, 47-51 and 53-54 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea ( without significantly more. The claims recite an abstract idea without significantly more because the additional elements fail to both integrate into a practical application or provide an inventive concept. Moreover, all claimed computer-based features fail eligibility steps 2A and 2B in not advancing computer technology, nor do the claimed features advance any other technology or technical field.
The eligibility analysis in support of these findings is provided below. Independent claim 1 is representative of all rejected claims and will be considered as an exemplar for these claims.
With respect to Step 1 of the eligibility inquiry, the processor-implemented method for managing one or more warehouses by a controller of claim 1 is ostensibly directed to an eligible category of subject matter, i.e. a process. Thus, Step 1 is satisfied.
With respect to Step 2A Prong One, the claims recite an abstract idea in the form of mental processes and a method of organizing human activity.
According to Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. In this case, the invention is primarily concerned with items b) and c).
Analysis of relevant limitations of claim 1 follows:
the method comprising: communicating with multiple tasks completion agents (TCAs) of the one or more warehouses to obtain information about said multiple TCAs, said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA,Communication is a method of human organization to the extent the TCAs are humans, and is an insignificant extra-solution activity (see analysis below) to the extent that TCAs are robots. The enumerated properties are merely data. Gathering information is a mental process.
wherein each TCA is configured to execute at least a task related to fulfillments of an order to obtain an item stored in the one or more warehouses, wherein the multiple TCAs comprise at least one type of TCAs differing from each other by capabilities with respect to one or more task related properties; wherein each type of TCAs comprises: (i) one or more autonomous robots, (ii) one or more human controlled robots and (iii) one or more humans;The TCAs of claim 1 are entities associated with warehouses about which information is to be gathered so that the claimed method may be performed. None of the information to be collected goes beyond the mental process a human subject could perform.
receiving multiple orders to obtain multiple items stored in the one or more warehouses;This is more information gathering, and again is routinely within the scope of human activity.
and utilizing a centralized computerized system for scheduling an execution of tasks related to the provision of the multiple items; wherein the scheduling comprises (i) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items;Scheduling is a mental process, and where the scheduling pertains to human TCAs, it is a method of human organization. The claimed use of a computer system does not change this analysis because computerization per se is an insignificant extra-solution activity per cases such as Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) and Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755.
wherein the allocating is based, at least in part, on said one or more task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;The determination of task related properties and spatial relationships of this limitation is a mental process; the former might be performed with the aid of a clipboard or binder, and the latter with a tape measure.
(ii) optimizing, based on said spatial relationships between the multiple items and the TCAs, an order of missions to be performed by the at least some of the allocated TCAs to optimize their path in the warehouse and to avoid lost times between missions and/or to minimize empty trips;Optimizing paths, in the absence of some further claims regarding the method of pathing or optimizing, is a mental process as a human can readily perform path optimization with pencil and paper. The claimed spatial relationships are mere data at this stage.
and (iii) communicating data with the allocated TCAs to control the execution of the tasks related to the provision of the multiple items, said data comprising an instruction for at least one of the following: one of the autonomous robots to complete a task, avoiding from guiding said autonomous robot during a completion of the task and waiting to receive a completion report from said autonomous robot; one of the human controlled robots to complete a task and guide said human controlled robot to complete said task.Again, communication is not considered to go beyond the realm of abstraction. This is the only limitation that pertains to the actual activity of TCAs, at least some of which are robots. The robots, however, are abstract machines, with no claimed structure, and which are only claimed to move on paths and complete similarly abstract tasks. Moreover, no details regarding the method of controlling TCA execution or the method of execution by the TCAs are claimed or disclosed, and so these steps are abstract in themselves. The newly amended negative step of not guiding an autonomous robot is at least an operational one during a period of time in which a robot is performing a task, but inasmuch as it does not comprise any actual activity it too is an abstraction. Refraining from issuing instructions and waiting for a machine’s task to conclude is also a human mental activity. Similarly, issuing a directive to a robot to complete a task is mere communication in the absence of some grounded aspect of the communication that constitutes or contributes to an invention.
All these limitations are within the scope of human capabilities. No special hardware or other inventive structure is claimed apart from some abstract robots that are merely black boxes without claimed structure and are taken to be generic. To the extent any computer system is disclosed by the limitations, per MPEP 2106.05(a) the invention does not “purport to improve the functioning of the computer itself” nor does its computer improve “any other technology or technical field.“ In particular, the courts have indicated that the mere automation of manual processes does not constitute an improvement in computer functionality (MPEP 2106.05(a)(I), second paragraph iii).
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements are directed to control of abstract “Task Completion Agents” (TCAs). This could have been done even in ancient times by a warehouse foreman or manager. No particular machine is claimed apart from black box robots (subtypes of TCA) that are considered to be on a par with human workers who are also TCAs, nor is the means of control or communication specified (though that alone would likely not repair the failure to integrate to a practical application). These elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to effect a transformation of a particular article to a different state or thing, and fail to apply or use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. We reconsider several of the new limitations in view of step 2B:
communicating with multiple tasks completion agents (TCAs) of the one or more warehouses to obtain information about said multiple TCAs, said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA,While adding more detail over the claim of the first action, these three properties are mere data, collecting the data is still information gathering, and communicating the data is still an abstract process.
(ii) optimizing, based on said spatial relationships between the multiple items and the TCAs, an order of missions to be performed by the at least some of the allocated TCAs to optimize their path in the warehouse and to avoid lost times between missions and/or to minimize empty trips;This limitation could perhaps add “significantly more” if the method of optimization were concretely claimed via (for example) an innovative algorithm that advances the computer arts, and if the method represented a process that could not be performed by a human; however in the actual case, no such claim or disclosure has been made. A human is generally capable of optimizing paths for robots and human workers.
and (iii) communicating data with the allocated TCAs to control the execution of the tasks related to the provision of the multiple items, said data comprising an instruction for at least one of the following: one of the autonomous robots to complete a task, avoiding from guiding said autonomous robot during a completion of the task and waiting to receive a completion report from said autonomous robot; one of the human controlled robots to complete a task and guide said human controlled robot to complete said task.This too is an abstract process of communication which also fails to add significantly more than the judicial exception.
These elements have been considered, but add nothing more to what is essentially a method of mental process and human organization.
Independent claim 47 is a non-transitory computer-readable storage medium claim and independent claim 49 is a system claim; both claims parallel method claim 1 and recite limitations of similar scope. Both claims are found to be similarly directed to patent-ineligible subject matter.
Dependent claims 8, 13-14, 17, 21, 26, 48, and 49-51, and 53-54 have been fully considered as well. The dependent claims add no inventive material substantially different from the analysis associated with claim 1; rather, they merely elaborate the method of the independent claims with more details, none of which add significant elements that transcend what are essentially mental processes and human organization. There is no indication that the combinations of elements in these claims improves the functioning of a computer or improves any other technology.
Claim Rejections - 35 USC § 103
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, 13-14, 17, 21, 26, 47-51 and 53-54 are rejected under 35 U.S.C. 103 as being unpatentable over Mason, et al., US 2016/0132059 (hereinafter Mason) in view of Kattepur, et al., US 2019/0049975 (hereinafter Kattepur) and further in view of Sarkar, et al., US 2019/0212753 (hereinafter Sarkar).
Regarding claim 1,
Mason discloses:
A processor-implemented method for managing one or more warehouses (fig. 1A, [0034]) by a controller (global control system 150: fig. 1B),
the method comprising: communicating with multiple tasks completion agents (TCAs) (robots 112, 114, 116, 122: fig. 1A) of the one or more warehouses to obtain information about said multiple TCAs, (data and information from robots, [0045])
wherein each TCA is configured to execute at least a task related to fulfillments of an order to obtain an item stored in the one or more warehouses, wherein the multiple TCAs comprise at least one type of TCAs differing from each other by capabilities with respect to said one or more task related properties (variety of robots seen in fig. 1A; data and information from robots, [0045]);
wherein each type of TCAs comprises: (i) one or more autonomous robots, (ii) one or more human controlled robots and (iii) one or more humans; (all three types of TCA, [0002])
and utilizing a centralized computerized system for scheduling an execution of tasks related to the provision of the multiple items; (central computer control, [0039]; tasks [0034]; scheduling, [0041])
(ii) optimizing, based on said spatial relationships between the multiple items and the TCAs, an order of missions to be performed by the at least some of the allocated TCAs to optimize their path in the warehouse (optimizing navigation plan based on space, [0041]) and to avoid lost times between missions and/or to minimize empty trips; and
(iii) communicating data (instructions from control system, [0065]) with the allocated TCAs to control the execution of the tasks related to the provision of the multiple items, said data comprising an instruction for at least one of the following: one of the autonomous robots to complete a task (optimizing navigation plan based on space, [0041]), avoiding from guiding said autonomous robot during a completion of the task and waiting to receive a completion report from said autonomous robot; one of the human controlled robots to complete a task and guide said human controlled robot to complete said task.Mason discloses at least the first of the three choices, instructing a robot to complete a task.
However, Mason does not disclose all aspects of:
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA,Mason does not disclose these properties.
receiving multiple orders to obtain multiple items stored in the one or more warehouses;Mason does not disclose fulfilling multiple orders together.
wherein the scheduling comprises: (i) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on said one or more task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;While Mason discloses the selection and assignment of robots to perform warehousing tasks in [0079] and elsewhere, while this selections is intended to optimize space considerations (“spatial relationships”) per [0041], and while this selection may be supposed to be performed on the basis of the different capabilities of the robots as disclosed for example in [0076], it does not explicitly disclose the selection on the basis of agent capabilities or task related properties.
Kattepur, an invention in the field of warehouse robotic fleet management, teaches:
receiving multiple orders to obtain multiple items stored in the one or more warehouses;Kattepur teaches batching multiple orders with multiple required products in [0033]. In combination with Mason, we retain Mason’s centralized control of all robot operations and incorporate other isolated aspects of Kattepur’s methods, including, for this limitation, the batching of multiple orders.
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA (load bearing capacity, [0032]); a progressive velocity of each TCA (average robot speed, [0072]),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason for, firstly, receiving multiple orders to obtain multiple items stored in the one or more warehouses, and secondly said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA, as taught by Kattepur. The first teaching is obvious because all warehouses involved in order fulfillment have to process multiple orders to obtain multiple items and because Kattepur (among many other published inventions) teaches order batching as part of optimizing in [0033]. The second teaching is obvious because given robots of different capabilities or task related properties such as taught by both Mason and Kattepur, the selection of a robot for a task on the basis of its capability necessarily leads to improvements in task and overall warehouse operational efficiency over a random selection. All robots capable of performing article transfer tasks have load capacities and average or maximum speeds, and so given that time is an optimization goal as taught by Mason, both these factors are plainly crucial to optimizing task completion time.
Sarkar, an invention in the field of multi-vehicle task allocation, teaches the missing aspects of:
wherein the scheduling comprises: (i) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on said one or more task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;
Sarkar introduces robot selection on the basis of maximum weight carrying capacity in [0027] and discloses a detailed method in [0030]-[0034].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason and Kattepur, wherein the scheduling comprises: (i) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on said one or more task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs, as taught by Sarkar, because as noted in the rationale for Kattepur immediately above, the selection of a robot on the basis of carrying capacity is crucial when optimizing tasks involving the picking and transport of articles in a warehouse, and this selection is equally crucial when performed in the context of scheduling.
Regarding claim 13,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 1 and also:
wherein the scheduling of the execution of tasks comprises at least one of (i) prioritizing orders based on due dates of the orders; (ii) minimizing an effort related to the execution of the tasks; (iii) optimizing the execution of the tasks related to the provision of the multiple items or (iv) allocating path route segments within the one or more warehouses to an execution of the tasks.Mason teaches several of these forms of optimization in [0041] and [0045].
Regarding claim 14,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 1 and also:
wherein the controlling of the execution of the tasks comprises at least one of (i) monitoring an execution of the tasks related to the provision of the multiple items or (ii) changing the allocation.Kattepur discloses in step 10 of table “Algorithm 1” between [0077] and [0078] that its coordinator receives reports of robotic task completion. This constitutes monitoring the execution of a task.
Regarding claim 17,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 1 and also:
wherein the controlling of the execution of the tasks comprises at least one of (i) monitoring an execution of the tasks related to the provision of the multiple items or (ii) changing the allocation.Kattepur discloses its method allocates tasks to robotic agents based on item accessibility (closeness of the robot to the shelves) in [0031] and also discloses in [0031] that inventory is monitored, which determines whether an item is available. Kattepur also discloses in [0090]-[0091] circumstances that can lead to the reallocation of a robotic agent.
Regarding claim 21,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 17 and also:
wherein the changing of the allocation is performed in response to an occurrence of a fault in a TCA.Kattepur discloses fault detection and reallocation of robotic agents in response in [0090]-[0091].
Regarding claim 26,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 1 and also:
wherein the at least one task comprises at least one out of unloading trucks, depalletizing, storing pallets, moving pallets, storing boxes, moving boxes, picking items, cycle counting, replenishing, packing, shipping, folding and or conveying.Kattepur discloses picking agents (i.e. for picking items) and delivery agents (i.e. for moving items or containers) in [0049]. Of course, all the claimed tasks are routine in a wide variety of robot-staffed warehouses long known to the art.
Regarding claim 47,
Mason discloses:
A non-transitory computer readable medium ([0118]) that stores instructions that once executed by a computerized system (global control system 150: fig. 1B) causes the computerized system to manage one or more warehouses (fig. 1A, [0034]),
by: communicating with multiple tasks completion agents (TCAs) (robots 112, 114, 116, 122: fig. 1A) of the one or more warehouses to obtain information about said multiple TCAs (data and information from robots, [0045]),
wherein a TCA is configured to execute a task related to fulfillments of an order to obtain an item stored in one or more warehouses, wherein the multiple TCAs comprise at least one type of TCAs differing from each other by capabilities with respect to one or more task related properties, (variety of robots seen in fig. 1A; data and information from robots, [0045])
wherein each type of TCAs comprises: (i) one or more autonomous robots, (ii) one or more human controlled robots and (iii) one or more humans; (all three types of TCA, [0002])
scheduling an execution of tasks related to the provision of the multiple items; (tasks [0034]; scheduling, [0041])
(ii) optimizing, based on said spatial relationships between the multiple items and the TCAs, an order of missions to be performed by the at least some of the allocated TCAs to optimize their path in the warehouse (optimizing navigation plan based on cost, [0030]) and to avoid lost times between missions and/or to minimize empty trips; and
(iii) communicating data with the allocated TCAs to control controlling the execution of the tasks related to the provision of the multiple items, said data comprising an instruction for at least one of the following: one of the autonomous robots to complete a task (control of pathing for task, [0034]), avoiding from guiding said autonomous robot during a completion of the task and waiting to receive a completion report from said autonomous robot; one of the human controlled robots to complete a task and guide said human controlled robot to complete said task.
However, Mason does not disclose all aspects of:
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA,Mason does not disclose these properties.
receiving in said computerized system multiple orders to obtain multiple items stored in the one or more warehouses;Mason does not disclose fulfilling multiple orders.
allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items; wherein the allocating is based, at least in part, on said task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAsWhile Mason discloses the selection and assignment of robots to perform warehousing tasks in [0079] and elsewhere, while this selections is intended to optimize space considerations (“spatial relationships”) per [0041], and while this selection may be supposed to be performed on the basis of the different capabilities of the robots as disclosed for example in [0076], it does not explicitly disclose the selection on the basis of agent capabilities or task related properties.
Kattepur, an invention in the field of warehouse robotic fleet management, teaches:
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA (load bearing capacity, [0032]); a progressive velocity of each TCA (average robot speed, [0072]),
receiving in said computerized system multiple orders to obtain multiple items stored in the one or more warehouses;Kattepur teaches batching multiple orders with multiple required products in [0033]. In combination with Mason, we retain Mason’s centralized control of all robot operations and incorporate other isolated aspects of Kattepur’s methods, including, for this limitation, the batching of multiple orders.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason and Kattepur for receiving in said computerized system multiple orders to obtain multiple items stored in the one or more warehouses, as taught by Kattepur, because all warehouses involved in order fulfillment have to process multiple orders to obtain multiple items and because Kattepur (among many others) teaches order batching as part of optimizing in [0033].
Sarkar, an invention in the field of multi-vehicle task allocation, teaches the missing aspects of:
allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items; wherein the allocating is based, at least in part, on said task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;
Sarkar introduces robot selection on the basis of maximum weight carrying capacity in [0027] and discloses a detailed method in [0030]-[0034].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason and Kattepur, allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items; wherein the allocating is based, at least in part, on said task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs, as taught by Sarkar, because as noted in the rationale for Kattepur immediately above, the selection of a robot on the basis of carrying capacity is crucial when optimizing tasks involving the picking and transport of articles in a warehouse, and this selection is equally crucial when performed in the context of scheduling.
Regarding claim 49,
Mason discloses:
A system (figs. 1A-B) for managing one or more warehouses (fig. 1A, [0034]),
the system comprising: multiple tasks completion agents (TCAs) (robots 112, 114, 116, 122: fig. 1A) of said one or more warehouses, wherein each TCA is configured to execute a task related to fulfillments of an order to obtain an item stored in the one or more warehouses, wherein the multiple TCAs comprises at least one type of TCAs differing from each other by capabilities (data and information from robots, [0045]) with respect to one or more task related properties;
a controller (global control system 150: fig. 1B) being configured and operable to: (i) communicate with said multiple TCAs of said one or more warehouses to obtain information about said multiple TCAs, (variety of robots seen in fig. 1A; data and information from robots, [0045])
wherein each type of TCAs comprises: (i) one or more autonomous robots, (ii) one or more human controlled robots and (iii) one or more humans; (all three types of TCA, [0002])
(iii) schedule an execution of tasks related to the provision of the multiple items (tasks [0034]; scheduling, [0041]);
(b) optimizing, based on said spatial relationships between the multiple items and the TCAs, an order of missions to be performed by the at least some of the allocated TCAs to optimize their path in the warehouse (optimizing navigation plan based on space, [0041]) and to avoid lost times between missions and/or to minimize empty trips; and
(c) communicating data (instructions from control system, [0065]) with the allocated TCAs to control the execution of the tasks related to the provision of the multiple items, said data comprising an instruction for at least one of the following: at least one of the autonomous robots to complete a task (optimizing navigation plan based on space, [0041]), avoiding from guiding said autonomous robot during a completion of the task and waiting to receive a completion report from said autonomous robot; and/or at least one of the human controlled robots to complete a task and guide said human controlled robot to complete said task.Mason discloses at least the first of the three choices, instructing a robot to complete a task.
However, Mason does not disclose all aspects of:
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA;Mason does not disclose these properties.
(ii) receive multiple orders to obtain multiple items stored in the one or more warehouses;Mason does not disclose fulfilling multiple orders.
wherein the scheduling comprises: (a) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;While Mason discloses the selection and assignment of robots to perform warehousing tasks in [0079] and elsewhere, while this selections is intended to optimize space considerations (“spatial relationships”) per [0041], and while this selection may be supposed to be performed on the basis of the different capabilities of the robots as disclosed for example in [0076], it does not explicitly disclose the selection on the basis of agent capabilities or task related properties.
Kattepur, an invention in the field of warehouse robotic fleet management, teaches:
said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA (load bearing capacity, [0032]); a progressive velocity of each TCA (average robot speed, [0072]);
(ii) receive multiple orders to obtain multiple items stored in the one or more warehouses;Kattepur teaches batching multiple orders with multiple required products in [0033]. In combination with Mason, we retain Mason’s centralized control of all robot operations and incorporate other aspects of Kattepur’s methods, including, for this limitation, the batching of multiple orders.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason for firstly, (ii) receive multiple orders to obtain multiple items stored in the one or more warehouses; and secondly, said information comprising one or more of the following task related properties: a reach zone of each TCA; a load capacity of each TCA; a progressive velocity of each TCA, as taught by Kattepur. The first teaching is obvious because all warehouses involved in order fulfillment have to process multiple orders to obtain multiple items and because Kattepur (among many other published inventions) teaches order batching as part of optimizing in [0033]. The second teaching is obvious because given robots of different capabilities or task related properties such as taught by both Mason and Kattepur, the selection of a robot for a task on the basis of its capability necessarily leads to improvements in task and overall warehouse operational efficiency over a random selection. All robots capable of performing article transfer tasks have load capacities and average or maximum speeds, and so given that time is an optimization goal as taught by Mason, both these factors are plainly crucial to optimizing task completion time.
Sarkar, an invention in the field of multi-vehicle task allocation, teaches the missing aspects of:
wherein the scheduling comprises: (a) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs;
Sarkar introduces robot selection on the basis of maximum weight carrying capacity in [0027] and discloses a detailed method in [0030]-[0034].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason and Kattepur, wherein the scheduling comprises: (a) allocating at least some of the multiple TCAs to execute tasks related to the provision of the multiple items, wherein the allocating is based, at least in part, on task related properties of the at least some of the multiple TCAs and on spatial relationships between the multiple items and the TCAs; as taught by Sarkar, because as noted in the rationale for Kattepur immediately above, the selection of a robot on the basis of carrying capacity is crucial when optimizing tasks involving the picking and transport of articles in a warehouse, and this selection is equally crucial when performed in the context of scheduling.
Regarding claim 50,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 49 and also:
wherein the TCAs comprise robots (Mason, 112, 114, 116, 122: fig. 1A) of different types.Mason teaches a wide variety of types of cooperating robots in its fig. 1A.
Regarding claim 51,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 49 and also:
wherein the TCAs comprise at least one of one or more drones, one or more ground-propagating robots or one or more static robots. Mason teaches both wheeled and tracked (“ground-propagating”) and static robots in fig. 1A.
Regarding claim 53,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 49 and also:
wherein said controller comprises a centralized computerized system being configured and operable to executing the scheduling and the controlling of the execution of tasks.Mason discloses its global control system 150 performs this function in [0039]-[0043].
Regarding claim 54,
Mason in view of Kattepur and Sarkar teaches the limitations of claim 53 and also:
wherein said centralized computerized system is configured and operable to distribute missions, tasks or routes to the TCAs, enabling the TCAs to collaborate and to perform a series of tasks.Mason discloses its global control system 150 performs this function in [0039]-[0043].
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Mason in view of Kattepur and Sarkar and further in view of Adato, et al., US 2019/0149725 (hereinafter Adato).
Mason in view of Kattepur and Sarkar teaches the limitations of claim 1, but not all aspects of:
wherein the allocating comprises allocating a human to execute a task that is not-executable by any of the one or more autonomous robots or of the human controlled robots.While the combination of Mason, Kattepur and Sarkar, which selects appropriate agents for tasks and also teaches that human may perform certain tasks, might imply the assignment of a human to a task that cannot be performed by a robot, we invoke a third reference to make this teaching explicit.
Adato, an invention in the field of image capturing, teaches:
wherein the allocating comprises allocating a human to execute a task that is not-executable by any of the one or more autonomous robots or of the human controlled robots.Adato teaches in [0674] that in a mixed group of human and robotic employees, robots may be selected first for a task if they are capable of performing it, and humans only assigned the task if robots are incapable.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason, Kattepur and Sarkar, wherein the allocating comprises allocating a human to execute a task that is not-executable by any of the one or more autonomous robots or of the human controlled robots, as taught by Adato, because it is often the case that robots are more efficient at performing repetitive tasks than humans, and so human resources should be reserved only for tasks that robots cannot complete. A person of ordinary skill in the art would recognize the cost-savings benefits of this method.
Claim 48 is rejected under 35 U.S.C. 103 as being unpatentable over Mason in view of Kattepur and Sarkar and further in view of Hodak, Max, US 2015/0242395 (hereinafter Hodak).
Mason in view of Kattepur and Sarkar teaches the limitations of claim 13, but not all aspects of:
wherein the optimizing of the execution of the tasks comprises at least one of (i) reducing lost time between tasks assigned to same TCA; (ii) reducing futile TCA trips.While the references teach a variety of means of optimizing robotic fleet task execution with respect to time and it could perhaps be argued that they reduce lost time between tasks assigned to the same TCA, they do not explicitly disclose either of the claimed types of optimization.
Hodak, an invention in the field of equipment sharing, teaches:
wherein the optimizing of the execution of the tasks comprises at least one of (i) reducing lost time between tasks assigned to same TCA; (ii) reducing futile TCA trips.Hodak teaches time-based optimization in [0052] and [0124], both approaches seeking to reduce lost time.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the system and method of Mason, Kattepur and Sarkar, wherein the optimizing of the execution of the tasks comprises at least one of (i) reducing lost time between tasks assigned to same TCA; (ii) reducing futile TCA trips, as taught by Hodak, because time-based optimization is one of the most common forms of efficiency improvement in the industrial arts and it is plain how reducing lost time saves operating costs in virtually any commercial or industrial context.
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 2022/0197304 teaches the selection of robots in a fleet for tasks based on grasp or reach capability.
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/ERNESTO A SUAREZ/Supervisory Patent Examiner, Art Unit 3655
LAURENCE RAPHAEL BROTHERS
Examiner
Art Unit 3655A
/L.R.B./ Examiner, Art Unit 3655
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