Prosecution Insights
Last updated: April 19, 2026
Application No. 19/010,403

INFORMATION PROVIDING SYSTEM AND INFORMATION PROVIDING METHOD

Non-Final OA §101§102
Filed
Jan 06, 2025
Examiner
SCHEUNEMANN, RICHARD N
Art Unit
3624
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Toyota Jidosha Kabushiki Kaisha
OA Round
1 (Non-Final)
6%
Grant Probability
At Risk
1-2
OA Rounds
4y 7m
To Grant
15%
With Interview

Examiner Intelligence

Grants only 6% of cases
6%
Career Allow Rate
35 granted / 551 resolved
-45.6% vs TC avg
Moderate +8% lift
Without
With
+8.4%
Interview Lift
resolved cases with interview
Typical timeline
4y 7m
Avg Prosecution
56 currently pending
Career history
607
Total Applications
across all art units

Statute-Specific Performance

§101
37.4%
-2.6% vs TC avg
§103
37.6%
-2.4% vs TC avg
§102
9.3%
-30.7% vs TC avg
§112
15.1%
-24.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 551 resolved cases

Office Action

§101 §102
DETAILED ACTION Introduction This Non-Final Office Action is in response to the application with serial number 19/010,403, filed on January 6, 2025. Claims 1-5 are pending. Information Disclosure Statement The information disclosure statement filed on January 6, 2025, has been considered. 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. The Manual of Patent Examining Procedure (MPEP) provides detailed rules for determining subject matter eligibility for claims in §2106. Those rules provide a basis for the analysis and finding of ineligibility that follows. Claims 1-5 are rejected under 35 U.S.C. 101. The claimed invention is directed to non-statutory subject matter because the claimed invention recites a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Under Step 1 of the subject matter eligibility analysis, claims(s) 1-5 are all directed to one of the four statutory categories of invention. However, under step 2A, prong one, the claims recite a judicial exception: providing information about an autonomous mobile robot (as evidenced by the preamble of exemplary independent claim 1), an abstract idea. Certain methods of organizing human activity are ineligible abstract ideas, including managing personal behavior or relationships or interactions between people. Additionally, note that mathematical concepts, including mathematical calculations, are ineligible abstract ideas. See MPEP §2106.04(a). The limitations of exemplary claim 1 include: “receiving input information . . . about a plurality of robot accessory units;” “perform a calculation process;” and “output a result calculated by the calculation process.” The steps are all steps for managing personal behavior and/or making calculations that, when considered alone and in combination, are part of the abstract idea of providing information about an autonomous mobile robot. The dependent claims further recite steps for managing personal behavior that are part of the abstract idea of providing information about an autonomous mobile robot. These claim elements, when considered alone and in combination, are considered to be abstract ideas because they are directed to a method of organizing human activity which includes managing a fleet of service providing vehicles to efficiently satisfy demand for services. Under step 2A, prong two, of the subject matter eligibility analysis, a claim that recites a judicial exception must be evaluated to determine whether the claim provides a practical application of the judicial exception. Additional elements of the independent claims amount to generic computer hardware that does not provide a practical application (a system with no particular hardware in independent claim 1; and a computer in independent claim 5). See MPEP §2106.04(d)[I]. Mobile robots are recited, but the robots do not perform the steps of the claims, and the robots have not particular structure. Therefore, the robots do not constitute a particular machine. The claims do not recite an improvement to another technology or technical field, nor do they recite an improvement to the functioning of the computer itself. See MPEP §2106.05(a). Because the claims only recite use of a generic computer, they do not apply the judicial exception with a particular machine. See MPEP §2106.05(b). Under step 2B of the subject matter eligibility analysis, the claims do not integrate the abstract idea into a judicial exception. Referring to the additional elements provided in the analysis in step one, above, the generic computer hardware does not provide significantly more than the recited abstract idea. See MPEP §2106.05(f). For these reasons, the claims do not provide a practical application of the abstract idea, nor do they amount to significantly more than an abstract idea under step 2B of the subject matter eligibility analysis. Using a generic computer to implement an abstract idea does not provide an inventive concept. Therefore, the claims recite ineligible subject matter under 35 USC §101. Claim Rejections - 35 USC § 102 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)(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. Claim(s) 1-5 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 11615353 B2 to Monovich et al. (hereinafter ‘MONOVICH’). Claim 1 MONOVICH discloses an information providing system that provides information about an autonomous mobile robot (see col 52, ln 21-36 and col 126, ln 3-21; an autonomous vehicle, drone, or car), the information providing system being configured to: receive input information including information about a plurality of robot accessory units that enables the autonomous mobile robot to execute a plurality of different services when used in combination with the autonomous mobile robot (see again col 126, ln 3-21; the scheduling delivery of the at least one additional part may include booking or assigning an autonomous vehicle (e.g., a drone or an autonomous car) for delivering the at least one additional part), information about a location where the autonomous mobile robot operates (see col 1, ln 55-col 2, ln 15; a location associated with a task), and information about a type of a service requested (see col 2, ln 33-54; the set of requests is associated with a number of task types. A scheduling weight for task types); perform a calculation process of calculating resource information based on the input information, the resource information being information about a resource amount for the autonomous mobile robot and the robot accessory units required for a service (see col 1, ln 26-37 and col 21, ln 17-col 22, ln 48; match available resources to the tasks to be performed. Detect and resolve discrepancies between high level and low level resource allocation numbers. Allocate enough resources to satisfy demand for a region. Cover enough demand for a specific task type. See also col 39, ln 40-col 40, ln 10; the available resources may include the field professionals themselves, working hours, vehicles, tools, equipment, spare parts, office space, and more.); and output a result calculated by the calculation process (see again col 21, ln 17-col 22, ln 48; generate a plan schedule that satisfies resource demands for task types. See also col 39, ln 40-col 40, ln 10; the available resources may include the field professionals themselves, working hours, vehicles, tools, equipment, spare parts, office space, and more.). Claim 2 MONOVICH discloses the information providing system according to claim 1. MONOVICH further discloses wherein the calculation process includes calculating, as a part of the resource information, information including information about a necessary human resource amount based on the input information (see col 39, ln 40-col 40, ln 10; the available resources may include the field professionals themselves, working hours, vehicles, tools, equipment, spare parts, office space, and more. See also col 21, ln 64- col 22, ln 49; schedule planner updates information in the human resources, finance, and other systems). Claim 3 MONOVICH discloses the information providing system according to claim 1. MONOVICH further discloses wherein the calculation process includes calculating the resource information based on the input information for each of a plurality of combinations of the autonomous mobile robot and the robot accessory units required for a service (see col 19, ln 37-col 20, ln 24 & col 24, ln 18-30; the decision inherent in answering a customer demand. While some of the data used comes from analysis module 441, forecasting module 442 may be used as a decision-making tool letting managers define their expectations (out of the different possible predictions and scenarios) and commit to the decision that planning should proceed in a manner consistent with these decisions. What-if analysis and managing different scenarios concurrently). Claim 4 MONOVICH discloses the information providing system according to claim 1. MONOVICH further discloses wherein the different services include at least two of a transport service (see col 126, ln 3-21; The autonomous vehicle may be part of a transportation service, such as Uber™, Lyft™, and Via™), a patrol service, and a cleaning service (see col 12, ln 27-54; distribute resources in the field. In property maintenance, field professionals may be individuals who are dispatched for landscaping, irrigation, and home and office cleaning). Claim 5 MONOVICH discloses an information providing method for a computer (see col 1, ln 55-col 2, ln 15; computer readable media and a processor) to provide information about an autonomous mobile robot (see col 52, ln 21-36 and col 126, ln 3-21; an autonomous vehicle, drone, or car), the information providing method comprising: receiving input information including information about a plurality of robot accessory units that enables the autonomous mobile robot to execute a plurality of different services when used in combination with the autonomous mobile robot (see again col 126, ln 3-21; the scheduling delivery of the at least one additional part may include booking or assigning an autonomous vehicle (e.g., a drone or an autonomous car) for delivering the at least one additional part), information about a location where the autonomous mobile robot operates (see col 1, ln 55-col 2, ln 15; a location associated with a task), and information about a type of a service requested (see col 2, ln 33-54; the set of requests is associated with a number of task types. A scheduling weight for task types); performing a calculation process of calculating resource information based on the input information, the resource information being information about a resource amount for the autonomous mobile robot and the robot accessory units required for a service (see col 1, ln 26-37 and col 21, ln 17-col 22, ln 48; match available resources to the tasks to be performed. Detect and resolve discrepancies between high level and low level resource allocation numbers. Allocate enough resources to satisfy demand for a region. Cover enough demand for a specific task type. See also col 39, ln 40-col 40, ln 10; the available resources may include the field professionals themselves, working hours, vehicles, tools, equipment, spare parts, office space, and more.); and outputting a result calculated by the calculation process (see again col 21, ln 17-col 22, ln 48; generate a plan schedule that satisfies resource demands for task types. See also col 39, ln 40-col 40, ln 10; the available resources may include the field professionals themselves, working hours, vehicles, tools, equipment, spare parts, office space, and more.). Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 12386361 B2 to Cord et al. A method of managing a fleet of autonomous parking robots is disclosed that provides the location of the robots. The method is taught to be a service that is managed by a service manager. See claim 1. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RICHARD N SCHEUNEMANN whose telephone number is (571)270-7947. The examiner can normally be reached M-F 9am-5pm EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Patricia Munson can be reached at 571-270-5396. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /RICHARD N SCHEUNEMANN/ Primary Examiner, Art Unit 3624
Read full office action

Prosecution Timeline

Jan 06, 2025
Application Filed
Mar 19, 2026
Non-Final Rejection — §101, §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
6%
Grant Probability
15%
With Interview (+8.4%)
4y 7m
Median Time to Grant
Low
PTA Risk
Based on 551 resolved cases by this examiner. Grant probability derived from career allow rate.

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