Prosecution Insights
Last updated: April 19, 2026
Application No. 18/116,924

PORTABLE SURVEY UNIT AND METHOD

Non-Final OA §103
Filed
Mar 03, 2023
Examiner
DO, TRUC M
Art Unit
3658
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Hyster-Yale Group Inc.
OA Round
3 (Non-Final)
82%
Grant Probability
Favorable
3-4
OA Rounds
2y 12m
To Grant
90%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allow Rate
544 granted / 660 resolved
+30.4% vs TC avg
Moderate +7% lift
Without
With
+7.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 12m
Avg Prosecution
37 currently pending
Career history
697
Total Applications
across all art units

Statute-Specific Performance

§101
9.2%
-30.8% vs TC avg
§103
50.6%
+10.6% vs TC avg
§102
22.9%
-17.1% vs TC avg
§112
15.9%
-24.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 660 resolved cases

Office Action

§103
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION This is a 2nd non-final Office Action on the merits in response to communications filed by Applicant on January 07, 2026. Claims 1-20 are currently pending and examined below. Response to Arguments In respond to applicant's arguments with respect to 35 U.S.C. 103 rejections of said previous office action have been fully considered and found to be persuasive that Holwell forklift vehicle 100 with the sensors 112S are part of the vehicle and not part of the pallets 610. 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 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 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Holwell et al. US2021/0141368 (“Holwell”) in view of Lee et al. US2013/0324152 (“Lee”) and further in view of Hance et al. US2018/0029797 (“Hance”). Regarding claim(s) 1, 8, 15. Holwell discloses a survey unit, said survey unit (e.g. pallet), the survey unit comprising: a platform (170) configured to be carried around the facility (fig. 1-fig. 4, pallet 610, para. 25, The sensors 112S are configured to detect a predetermined characteristic of at least one pallet 610A-610C located in a stack (or column) 500 of one or more pallets (i.e., a pallet stack) (see FIGS. 5A-5C noting that while three pallets are illustrated any suitable number of pallets may be stacked one on top of the other in the pallet stack 500).), comprising load location information that can be used by an AGV to pick or to drop loads at the load locations (para. 43, Referring to FIGS. 1 and 5A-5D, the autonomous guided vehicle 100 is configured to navigate through the travel area 198 of the commercial logistic facility 199 in any suitable manner, such as along travel path 599 to a location, which in one aspect is a variable location, of the pallet stack 500. The travel path 599 may have any suitable waypoints or staging areas along the travel path 599.) Holwell does not explicitly disclose a plurality of visual and locational sensors located on the platform and configured to collect data related to the load locations in the facility (e.g. sensor located on a pallet configured to collect location data) Lee teaches an asset tracking system and method that has a sensor on a pallet configured to collect data relation to load locations ([0033-0034] Transmitter device 14 is secured to asset 12, for example, on pallet 13 on which is loaded goods; in some embodiments, device 14 may be secured to pallet 13 in a manner that does not readily allow removal of device 14 from pallet 13. Transmitter device 14 also includes a positioning element, in these embodiments a GPS positioning element 30 connected to an antenna 31, which may be an internal antenna or an external antenna. Positioning element 30 provides data to transmitter device 14A, 14B regarding its physical location. When device 14A, 14B transmits data (i.e., pings), this location can then be transmitted to display 18.) It would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the system and method of Holwell by incorporating the applied teaching of Lee above to improve inventory management and assets tracking in an warehousing environment and one of ordinary skill in the art would have recognized that the results of the combination would have been predictable. Holwell also silent to using the collected data is sufficient to create a facility map. Hance teaches another inventory management system and method that using collected data is sufficient to create a facility map (para. 62, a warehouse management system may dynamically update a map of the physical environment containing robotic fleet 100 and objects undergoing processing by the robotic devices. In some examples, the map may be continuously updated with information about dynamic objects (e.g., moving robots and packages moved by robots). In additional examples, a dynamic map could contain information on both the current configuration or placement of components within a warehouse (or across multiple warehouses) as well as information about what is anticipated in the near term… the map could show the current location of all items within the warehouse (or across multiple warehouses).) Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to further modify the system and method of Holwell by incorporating the applied teaching of Hance above to improve inventory management by dynamically updating the map of the facility and one of ordinary skill in the art would have recognized that the results of the combination would have been predictable. Regarding claim(s) 2, 9, 16. Holwell in view of Lee and Hance further teaches a software module configured to use the collected data to create the facility map (para. 24, close coupling between the autonomous guided vehicle 100 (and its payload and/or accessory module) with manufacturing equipment, etc., and/or simultaneous localization and mapping (SLAM) (or other suitable navigation technique) within the commercial logistic facility 199.) Regarding claim(s) 3, 10. Holwell in view of Lee and Hance further teaches a communications module configured to communicate the collected data to a software module configured to use the collected data to create the facility map (para. 25, Referring to FIGS. 1, 2, 7A-7C, 9A, and 9B, the sensors 112 may also include any suitable sensors 112S that are communicably connected to the robotic autonomous guided vehicle engine module 110 in any suitable manner. The sensors 112S are configured to detect a predetermined characteristic of at least one pallet 610A-610C located in a stack (or column) 500 of one or more pallets). Regarding claim(s) 4, 20. Holwell in view of Lee and Hance further teaches wherein the plurality of visual and locational sensors comprise a plurality of cameras and a LIDAR or RADAR unit (para. 30, The at least one sensing element 112S comprises one or more of, but is not limited to, a two-dimensional LIDAR (light detection and ranging) sensor, a three-dimensional LIDAR sensor, an RGB camera (CMOS or complementary metal oxide semiconductor sensor, CCD charge-coupled device sensor, etc.), a depth camera, a time-of-flight camera, stereo cameras or sets of cameras to effect at least binocular vision, etc.) Regarding claim(s) 5, 11. Holwell in view of Lee and Hance further teaches wherein the vehicle is a forklift, and wherein the housing comprises a box arranged on a pallet configured to be carried by the forks of the forklift when being used to collect data to create a facility map (Hance see claim 1). Regarding claim(s) 6. Holwell in view of Lee and Hance further teaches wherein the plurality of visual and locational sensors comprise a plurality of cameras, an infrared sensor, an inertial measurement unit, and a GPS unit (para. 30, The at least one sensing element 112S comprises one or more of, but is not limited to, a two-dimensional LIDAR (light detection and ranging) sensor, a three-dimensional LIDAR sensor, an RGB camera (CMOS or complementary metal oxide semiconductor sensor, CCD charge-coupled device sensor, etc.), a depth camera, a time-of-flight camera, stereo cameras or sets of cameras to effect at least binocular vision, etc.) Regarding claim(s) 7. Holwell in view of Lee and Hance further teaches a data storage unit; and a computing unit (para. 21, he autonomous guided vehicle 100 is configured for logistic and/or material handling in a commercial logistic facility 199. Examples of the commercial logistic facility 199 include, but are not limited to, warehouses, stores, storage and retrieval facilities, distribution facilities, and production/assembly facilities. Suitable examples of the autonomous guided vehicle 100.) Regarding claim(s) 12. Holwell in view of Lee and Hance further teaches wherein the forklift raises or lowers its forks as necessary to collect data related to load locations (para. 34, (see FIG. 3) that can stack pallet loads on top of one another, such as when stacking pallet loads in a conveyance vehicle or other suitable location. The pallet pick 600 is configured to move, in any suitable manner such as described herein, bi-directionally in one or more pick directions 222, 223 relative to the robotic autonomous guided vehicle engine module 110 to at least lower and raise a pallet pick interface 600INT (substantially similar to those shown in FIG. 3) of the pallet pick 600 to interface with, engage, and pick (or place) a pallet 610A-610C and stably hold the picked pallet 610A-610C on the pallet pick 600.) Regarding claim(s) 13. Holwell in view of Lee and Hance further teaches wherein transferring the collected data to the processing unit comprises transferring the data to an external device using a communications module arranged in the survey unit (para. 27, e, the pallet stack 500 is located in a predetermined location that is known by the controller 14 or communicated to the controller 14 by, for example, the management system 196 or other suitable input device connected to the autonomous guided vehicle 100. As described above, the predetermined location may be a variable location (e.g., the location of the pallet stack or area in which the pallet stack is formed may move from one location to another) within the commercial logistic facility 199 or a fixed/stationary location (e.g., the location of the pallet stack or area in which the pallet stack is formed does not move) within the commercial logistic facility 199.) Regarding claim(s) 14. Holwell in view of Lee and Hance further teaches loading the survey unit onto forks of the forklift before using the forklift to transport the survey unit around the facility; and moving the forks of the forklift up and down as necessary to collect data related to load locations (para. 49, to scan the pallet stack 500 or pallet(s) within the pallet stack 500 the controller 14 commands (in any suitable manner) the autonomous guided vehicle 100 to raise the pallet pick 600 in pick direction 223A (FIG. 6, Block 610) from the predetermined lower pallet (such as one or more of pallets 610B, 610C) to a predetermined higher pallet (such as pallet 610A) in the pallet stack 500.) Regarding claim(s) 17. Holwell in view of Lee and Hance further teaches wherein the computing unit comprises software for creating the facility map, said software comprising an augmented sensing device block, an observational filtering block, a warehouse cell association block, and a driveable area detection application (para. 43, Referring to FIGS. 1 and 5A-5D, the autonomous guided vehicle 100 is configured to navigate through the travel area 198 of the commercial logistic facility 199 in any suitable manner, such as along travel path 599 to a location, which in one aspect is a variable location, of the pallet stack 500. The travel path 599 may have any suitable waypoints or staging areas along the travel path 599.) Regarding claim(s) 18. Holwell in view of Lee and Hance further teaches wherein the augmented sensing device block is configured to identify objects and their positions from the sensor data (para. 28, a distance between the pallet pick interface 600INT and each of the at least one sensing element 112SE in the pick direction 223 is known to, e.g. the controller 114, and the pallet pick interface 600INT can be positioned in the pick direction 223 based on scan data obtained by the at least one sensing element 112SE.) Regarding claim(s) 19. Holwell in view of Lee and Hance further teaches wherein the driveable area detection application is configured to identify driveable areas within the facility from the sensor data (para. 22, such as where the autonomous guided vehicle 100 operates in a production/assembly facility (the production/assembly facility is used here for exemplary purposes only and it should be understood that the autonomous guided vehicle 100 may perform any suitable transport of goods depending on the facility in which the autonomous guided vehicle 100 operates), the autonomous guided vehicle may traverse a travel area 198 in the production/assembly facility to transport objects from/to or between different fabrication zones in the production/assembly facility where each different fabrication zone has a different stage of goods fabrication.) Inquiry Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRUC M DO whose telephone number is (571)270-5962. The examiner can normally be reached on 9AM-6PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramón Mercado, Ph.D. can be reached on (571) 270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /TRUC M DO/Primary Examiner, Art Unit 3658
Read full office action

Prosecution Timeline

Mar 03, 2023
Application Filed
Mar 22, 2025
Non-Final Rejection — §103
Jun 27, 2025
Response Filed
Oct 04, 2025
Final Rejection — §103
Nov 20, 2025
Response after Non-Final Action
Jan 07, 2026
Response after Non-Final Action
Feb 05, 2026
Non-Final Rejection — §103 (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

3-4
Expected OA Rounds
82%
Grant Probability
90%
With Interview (+7.2%)
2y 12m
Median Time to Grant
High
PTA Risk
Based on 660 resolved cases by this examiner. Grant probability derived from career allow rate.

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