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 .
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.
Claim 18 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non- statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed to “A computer program product comprising a computer program…”, which under its broadest reasonable interpretation can be interpreted as software per se. Moreover, software per se has been held to be non-statutory subject matter (MPEP 2106.03).
Claims 1-17 and 19-20 are rejected under 35 U.S.C. 101 as the claims are directed to a judicial exception (abstract idea) without significantly more.
In the instant case, claims 1-16 and 19-20 are directed to a method and claim 17 is directed a system comprising various modules. Therefore, these claims fall within the four statutory categories of invention.
These claims describe a dispatch method for a transport robot including the steps of
S1: assigning a heat value to each order in an order pool according to a picking friendliness index;
S2: selecting, in response to an order assignment demand, an order whose heat value meets a preset condition from the order pool; and
S3: generating a dispatch instruction for at least one transport robot based on the selected order.
These steps may be practically performed in the human mind with the aid of pen and paper and using observation, evaluation, judgment and/or opinion. For example, the claimed “dispatch” method is basically a scheduling system for transport robots and human operators based on a heat value, i.e., ranking, of a “picking friendliness index”. Applicant’s specification defines the picking friendliness index as a “human efficiency value index” (para. 11) and, moreover, the human mind is certainly capable of determining a heat value/index as the human mind can receive and evaluate various orders, use judgment to rank/prioritize the various orders based on efficiency criteria, and then send instructions related to scheduling to least one transport robot or human operator based on said ranking.
The claimed method steps thus define a process that can be grouped within the “mental processes” grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). See also MPEP 2106.04(a)(2).III. Mental Processes. Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 54-55 (January 7, 2019)), the additional element(s) of claim 17 such as the respective analysis, selection and order assignment modules can be viewed a generic computer elements. Further, the use of a processor/computer as a tool to implement the abstract idea does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claims also do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using the respective modules to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of dispatching instructions to a transport robot. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of scheduling based on efficiency criteria. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
Dependent claims 2-16 and 19-20 further describe variations of the main abstract idea. For example, claim 2 describes generating scheduling instructions to a human picker (claim 2); claim 3 describes using dynamic data to re-evaluate and re-rank each order; claims 7 and 8 describes determining an order ranking based on the clustering of said orders or the quantity of goods in said orders. These dependent claims can also be readily regarded as mental process steps and thus do not include additional elements that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. Therefore, the dependent claims are also not patent eligible.
For these reasons, claims 1-20 are rejected under 35 U.S.C. 101 and are not patent eligible.
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 5, 9, 15, 16 and 19-20 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 pre-AIA the applicant regards as the invention.
Regarding claims 5, 9, 15, 16 and 19-20, the phrasing “in particular” and “particularly in” is indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. Cf. MPEP § 2173.05(d).
Further, regarding claims 16 and 19-20, the language relating to “binding” and “non-binding” picking modes is indefinite even in light of the specification. That is, this language does not appear to be defined in the specification (Cf. para. 38 and 87) and does not appear to a be a term known in the art, thus these claims are regarded as unexaminable as the scope of the claim are indeterminate and thus unclear.
Examiner requests clarification and recommends amending the claims with language that clearly sets forth the claimed invention. In the interim, and in the interests of compact prosecution, the claims have been interpreted as set forth below.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention; or
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 7, 10-12, 15 and 17-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Walet et al. (“Walet”)(US 2022/0391813 A1).
Walet teaches a dispatch method for a transport robot, comprising the following steps:
(re: base claim 1) S1: assigning a heat value to each order in an order pool according to a picking friendliness index (para. 8, 11 teaching that each of the multiple warehouse workers are assigned a queue of tasks/orders, such as case picking or loading or unloading, that are each ranked by determining “whether the warehouse worker’s time and energy will be efficiently utilized”, thus-- as Applicant’s specification, para. 11, defines the picking friendliness index as a “human efficiency value index”—assigning a ranking based on how a worker’s time and energy is efficiently utilized can be regarded as assigning a heat value according to a picking friendliness, i.e., picking efficiency; see also para. 48-50 teaching that efficiency metrics are also applied to analysis and distribution of tasks to transport robots, i.e., forklifts);
S2: selecting, in response to an order assignment demand, an order whose heat value meets a preset condition from the order pool (fig. 4D showing that in response to initial step of Operator requesting/demanding a task in step 460, a task/order is selected and sent to operator based on condition of sending highest heat value task in respective Operator queue; see also para. 42-50 teaching that computer assigns task/order to forklift, after forklift request, based on efficiency metrics of transport robots/forklifts and para. 80 teaching that computer selects tasks based on highest-rank conditions); and
S3: generating a dispatch instruction for at least one transport robot based on the selected order (para. 36-37 teaching that dispatch instructions can be applied to both manual, i.e., operator, and automated warehouses, i.e., transport robot; see e.g., fig. 1 and para. 40-45 teaching that dispatch method involves determining “optimal task selection” and assignment for both forklifts and warehouse workers);
(re: claim 2) wherein step S3 further comprises: generating a dispatch instruction for at least one human picker based on the selected order (fig. 4D in step 462 teaching sending dispatch instruction to operator/warehouse worker);
(re: claim 3) wherein the picking friendliness index includes a static index and a dynamic index, the static index does not change with order contents in the order pool, while the dynamic index changes with the order contents in the order pool (para. 9, 45 teaching calculation of efficiency metric that is dynamic and changes with completion of tasks, such as pallet replenishment, and/or change in location);
(re: claim 7) wherein step S1 comprises: determining the heat value according to an aggregation degree of the picking locations corresponding to the goods included in the order (para. 43-48 teaching the optimization of task/order selecting involves analysis of travel time of respective transport robots to task location—thus aggregation degree, i.e., clustering of task locations, determines respective heat values);
(re: claim 10) wherein the dispatch method further comprises:
after sending the dispatch instruction to at least one transport robot and/or at least one human picker, monitoring in real time the picking efficiency, completeness of remaining orders, congestion rate, number of assigned transport robots and/or ratio of the number of transport robots to the number of human pickers in each work area, and
updating the dispatch instruction for at least one transport robot and/or at least one human picker based on monitoring results (para. 123, 133-139 teaching monitoring operator movement and task completion, wherein a new dispatch instruction is requested and sent);
(re: claim 11) wherein updating the dispatch instruction for at least one transport robot comprises:
updating a picking route; and/or
updating the dispatch instruction for at least one human picker comprises: instructing at least one human picker to leave a current work area (Id. wherein para. 139 teaching that new instructions may guide operator to a new work location);
(re: claim 12) wherein step S2 comprises: ranking the orders in the order pool according to their heat values, and selecting an order with the largest heat value in response to the order assignment demand (para. 80 teaching that computer selects tasks based on highest-rank conditions, wherein higher ranking is regarded as higher heat value);
(re: certain elements of claim 13) wherein step S3 comprises: sending order information and zone information a handheld communication device of at least one human picker, in order to guide the at least one human picker to pick up goods in the zone (para. 133-142 teaching that operator user device functions to receive task information, such as task list and warehouse identifier, wherein task information can include directions that guide operator from pick-up to destination location);
(re: certain elements of claim 14) wherein step S3 comprises:
assigning the at least one human picker, additionally based on a predicted travel distance and/or waiting time of individual human pickers:
to travel to a predetermined picking location within a current
(re: claim 15) wherein step S3 comprises:
generating the dispatch instruction additionally based on a moving speed of at least one transport robot, a picking speed and/or moving speed of at least one human picker, the number of remaining picking tasks of at least one human picker and/or in at least one work area,
wherein the dispatch instruction
Walet further teaches a dispatch system, said dispatch system being configured to perform the dispatch method according to claim 1, and the dispatch system comprising:
(re: claim 17) an analysis module, which is configured to assign a heat value to each order in an order pool according to a picking friendliness index;
a selection module, which is configured to select, in response to an order assignment demand, an order whose heat value meets a preset condition from the order pool; and
an order assignment module, which is configured to generate a dispatch instruction for at least one transport robot based on the selected order (fig. 6 and para. 149-164 teaching control system elements including processor 652 and memory include executable instructions for performing dispatch method cited above, wherein the specific modules are regarded as elements within control system elements for performing specific “analysis”, “selection” or “assignment” step).
Walet further teaches computer program product comprising
(re: claim 18) a computer program, which, when executed by a computer, performs the dispatch method according to claim 1 (Id. with para. 163-164 expressly teaching computer programs and machine instructions for implementing dispatch method).
Claim Rejections - 35 USC § 103
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 of this title, 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 4-6, 8 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Walet et al. (“Walet”)(US 2022/0391813 A1) in view of Rasmussen et al. (“Rasmussen”)(US 2021/0032029) and legal precedent.
Walet as set forth above teaches all that is claimed except for expressly teaching
(re: claim 4) wherein step S1 comprises:
obtaining a statistical distribution of goods included in each order in the order pool over picking positions;
selecting a certain number of picking locations based on the statistical distribution, and
extending at least one area outwardly from the certain number of picking locations as a hot zone; and
determining the heat value based on a proportion of the picking locations corresponding to the goods included in each order in the hot zone;
(re: claim 5) wherein the hot zone is in units of an aisle area including picking locations, wherein different hot zones differ from one another
(re: claim 6) wherein the statistical distribution is projected onto a warehouse map to generate a visual heat map, from which an area with the deepest color is selected as the hot zone;
(re: claim 8) wherein step S1 comprises: determining the heat value according to the quantity of the goods included in the order;
(re: certain elements of claim 13) wherein step S3 comprises: sending a picking list corresponding to the selected order and information of the hot zone;
(re: certain elements of claim 14) wherein travel distance includes to travel to a predetermined picking location within a current hot zone.
Rasmussen, however, teaches that it is well-known in the order fulfillment arts to create a visual heat map representing a statistical distribution of goods, i.e., order item counts located at various warehouse locations, as well as send visual instructions to an operator to assist in more efficient order completion (Cf. fig. 3 and 4 showing hot zones as different picking locations/nodes within aisles; para. 27-46 teaching that order algorithm ranks each node based on highest number of mapped items and then optimizes order pick-up via shortest pathway and priority orders, wherein the aisle areas with the highest ranking nodes can be regarded as hot zones and the visual display on a user interface allows an operator to receive visual guidance for traveling within the hot zone to pick up order items—wherein the user interface with pick-up instructions is regarded as “sending a picking list”).
Further, the claimed features relating to the choice of color for the visual heat map or heat value related to quantity of items or proportion of locations with goods can be regarded as common design parameters/operating variables controlled by the design incentives involved in this type of subject matter. Moreover, legal precedent teaches that variations in these type of common parameters/variables are obvious and are the mere optimization of result-effective variables that would be known to one with ordinary skill in the art. See MPEP 2144.05 I.II (teaching ample motivation to optimize or modify result-effective variables based on “design need(s)” or “market demand”); see also MPEP 2144.04.IV (teaching that changes in size, proportion or shape of known elements are obvious).
It would thus be obvious to one with ordinary skill in the art to modify the base reference with these prior art teachings—with a reasonable expectation of success—to arrive at the claimed invention. The rationale for this obviousness determination can be found in the prior art itself as cited above and in legal precedent as described above. Further, the prior art discussed and cited demonstrates the level of sophistication of one with ordinary skill in the art and that these modifications are predictable variations that would be within this skill level. Therefore, it would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the invention of Walet for the reasons set forth above.
Conclusion
Any references not explicitly discussed above but made of record are regarded as helpful in establishing the state of the prior art and are thus considered relevant to the prosecution of the instant application.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEPH C RODRIGUEZ whose telephone number is 571-272-3692 (M-F, 9 am – 6 pm, PST). The Supervisory Examiner is MICHAEL MCCULLOUGH, 571-272-7805.
Alternatively, to contact the examiner, send an E-mail communication to Joseph.Rodriguez@uspto.gov. Such E-mail communication should be in accordance with provisions of the MPEP (see e.g., 502.03 & 713.04; see also Patent Internet Usage Policy Article 5). E-mail communication must begin with a statement authorizing the E-mail communication and acknowledging that such communication is not secure and may be made of record. Please note that any communications with regards to the merits of an application will be made of record. A suggested format for such authorization is as follows: "Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with me concerning any subject matter of this application by electronic mail. I understand that a copy of these communications will be made of record in the application file”.
Information regarding the status of an application may also be obtained from the Patent Center: https://patentcenter.uspto.gov/
/JOSEPH C RODRIGUEZ/Primary Examiner, Art Unit 3655
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February 4, 2026