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 . Claims 1-20 are pending and examined below. This action is in response to the claims filed 4/17/26.
Continued Examination Under 37 CFR 1.114
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 4/17/26 has been entered.
Response to Amendment
Applicant’s arguments, see Applicant Remarks Claim Interpretation filed on 4/17/26, regarding 35 U.S.C. § 112(f) have been fully considered and are not found persuasive. The claim elements interpreted under 35 U.S.C. § 112(f) utilize generic placeholders without being modified by sufficient structure, material, or acts for performing the claimed function.
Applicant’s remarks asserts the 3 prong analysis was not sufficiently applied in the prior office actions. This does not sufficiently overcome the interpretation. The 3-prong analysis does require the interpretation as claimed:
The claim limitations use the terms “module” which is a generic placeholder used as a substitute for “means” having no specific structural meaning.
While the claim language for these “modules” does not explicitly utilize a transition word due to the grammatical structure of the claims, it still modifies the generic placeholder by functional language, “determining” and “adjusting” respectively as seen below
determining, using an external reference point detection module within the autonomous vehicle, an external reference point to the autonomous vehicle by
adjusting, using a docking module, a position of the autonomous vehicle in a first axis ...
Neither of the “modules” are modified by any structure, material, or acts for performing the claimed function
Therefore the 35 U.S.C. § 112(f) interpretations are maintained below.
Amending to include structure from the specification may overcome the 35 U.S.C. § 112(f) claim interpretation.
Applicant’s arguments, see Applicant Remarks 35 U.S.C. § 112(a) filed on 4/17/26, regarding 35 U.S.C. § 112(a) rejections are moot in view of amendments filed 4/17/26. 35 U.S.C. § 112(a) rejections are withdrawn.
Applicant’s arguments, see Applicant Remarks 35 U.S.C. § 103 filed on 4/17/26, regarding 35 U.S.C. § 103 rejections are persuasive in view of amendments filed 4/17/26.
However, upon further consideration, new grounds of rejection are made in view of Uraki (US 2021/0094580) below.
Additional note regarding the combination of Dodd in view of Uraki, Dodd discloses the utilization of a Lidar sensor to determine distance to externally identified objects, however, it does not disclose the actual processing steps of converting the raw lidar sensor data to clustering/distance determinations. The teachings of Uraki are relied upon to disclose those explicit processing steps which are implied in the lidar object detection system as one of ordinary skill in the art before the effective filing date would understand lidar object detection and range finding as utilized in Dodd.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Claim elements interpreted under 35 U.S.C. 112(f) as (C) generic placeholders not modified by sufficient structure, material, or acts for performing the claimed function include the following:
“an external reference point detection module”, interpreted as a processor via Specification ¶48-49
“a docking module”, interpreted as a processor via Specification ¶48-49
The detailed 3-prong analysis is shown below:
(A) The claim limitations use the terms “module” which is a generic placeholder used as a substitute for “means” having no specific structural meaning.
(B) While the claim language for these “modules” does not explicitly utilize a transition word due to the grammatical structure of the claims, it still modifies the generic placeholder by functional language, “determining” and “adjusting” respectively as seen below
a. determining, using an external reference point detection module within the autonomous vehicle, an external reference point to the autonomous vehicle by
b. adjusting, using a docking module, a position of the autonomous vehicle in a first axis ...
(C) Neither of the “modules” are modified by any structure, material, or acts for performing the claimed function
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, 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 1-3, 6-9, 11-14, 16-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dodd et al. (US 2019/0039425) in view of Uraki (US 2021/0094580).
Regarding claims 1, 13, and 20, Dodd discloses an autonomous docking system including a method/system/non-transitory computer program product storing instructions comprising (¶104):
at least one data processor; and memory storing instructions, which when executed by at least one data processor, result in operations for implementing operations comprising (¶104):
receiving, from an external data source, external data comprising (i) an indication that the autonomous vehicle is within a docking location, (ii) an adjustment distance to place the autonomous vehicle within a threshold distance of the docking location, and (iii) a plurality of data points (¶77-78 and ¶115-116 – determination of connection distance and closing distance corresponding to the recited indication that the autonomous vehicle is within a docking location where the closing distance is compared to a threshold distance to place the vehicle within a threshold distance of the docking location where the connection distance can utilize an externally provided GPS Latitude and Longitude navigation system corresponding to the recited external data from an external data source where the connection distance and closing distance both provide data points iteratively as the distance decreases corresponding to the recited plurality of data points);
determining, using an external reference point detection module within the autonomous vehicle, an external reference point to the autonomous vehicle (¶155 and Fig. 4A – reflector indicator corresponding to the recited external reference point being identified by the master controller corresponding to the recited external reference point detection module within the autonomous vehicle); and
incrementally adjusting, using a docking module, a position of the autonomous vehicle in a first axis based on a distance between the autonomous vehicle and the external reference point until either (i) the autonomous vehicle is within the threshold distance of the docking location or (ii) a number of adjustments exceeds an adjustment maximum (¶125, ¶140-146, and ¶155 – trajectory generation and self docking control corresponding to the recited incrementally adjusting position of the vehicle based on longitude, latitude, and orientation of the vehicle corresponding to the recited first and second axis in relation to the reflector indicator corresponding to the recited external reference point until contact with the intended target is made, where contact with the target is within any potential threshold distance. The “or” claim element only requires one of the grouping to be disclosed to teach the entirety of the claim as written).
While Dodd does disclose identifying the different points with Lidar sensors which identify objects and positions utilizing point cloud clustering, Dodd does not explicitly disclose the process of how the Lidar physically processes the data to identify the points.
However, Uraki explicitly discloses the process of using a Lidar sensors for detecting positioning of an autonomous vehicle control system including (i) generating a plurality of clusters from the plurality of data points based on distances between each data point, wherein each cluster comprises at least two data points and the external reference point is based on a cluster of the plurality of clusters (¶105-106 and ¶116-125 - LiDAR data analyzer 52 acquires the three-dimensional point group data (see FIG. 15) from the LiDAR 36. The LiDAR data analyzer 52 further executes clustering for grouping the three-dimensional points into at least one cluster where the reference cluster 80 corresponding to the recited external reference point is based on a cluster of the plurality of clusters); and
(ii) for each cluster of the plurality of clusters, determining a distance between the cluster and an internal reference point of the autonomous vehicle (¶105-106 and ¶116-125 – determining the distance between the LIDAR sensor corresponding to the recited internal reference point of the autonomous vehicle and the k-th cluster corresponding to the recited determining a relative distance for each cluster of the plurality of clusters); and
The combination of the autonomous docking system of Dodd with the explicit recitation of the lidar point cloud clustering and distance determination of Uraki fully discloses the elements as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the autonomous docking system of Dodd with the explicit recitation of the lidar point cloud clustering and distance determination of Uraki in order to determine the distance of objects from the vehicle and attributes of the objects to perform precise docking control in an automated driving vehicle (Uraki - ¶6-8).
Regarding claims 2 and 14, Dodd further discloses wherein the threshold distance is less than 5 centimeters of a boundary in the first axis of the docking location (¶125 – contact with the intended target corresponding to the recited threshold distance being less than 5 centimeters of a boundary in the first axis of the docking location).
Regarding claim 3, Dodd further discloses wherein the plurality of data points comprise a plurality of light and detection ranging (LiDAR) data points (¶155 - In camera, LIDAR, VORAD or other systems, determining the points and distances does not require cross-talk to establish communications, rather the camera, laser or radar devices on the vehicle V1, V1TG1 establish that they have found an indicator on the target TG2 that sets the points D1, D2, such as a visual indicator, reflector, or other known detectable mechanism).
Regarding claims 6 and 16, Dodd further discloses wherein the external reference point has a light reflectivity that is of higher intensity than nearby surroundings of the external reference point (¶155 – reflector indicator corresponding to the recited external reference point has a light reflectivity that is of higher intensity than nearby surroundings of the external reference point).
Regarding claims 7, 8, 9, and 17, Dodd further discloses the position is incrementally adjusted through an iterative series of applying and releasing a braking mechanism of the autonomous vehicle by (¶86-88, ¶130, and Figs. 5A and 6D –speed is iteratively adjusted by applying/releasing/ramping of brake pressure to move the vehicle forward):
determining a brake release duration, wherein the brake release duration is an amount of time where a brake of the autonomous vehicle is at least partially released (¶86-88, ¶130, and Figs. 5A and 6D – timer applying a limit to the amount of time for commanding the increase in vehicle speed which starts at element 630 with the vehicle brake release where the duration of time for increasing or decreasing speed is determined to modulate the amount of braking force to be applied or released and for how long in order to control and maintain the vehicle speed as it approaches the dock);
releasing a braking mechanism for a portion of the brake release duration (¶86-88, ¶130, and Figs. 5A and 6D – if the timer is not exceeded at S580 while applying sloped release of brakes (element 651) then the braking mechanism is released for a portion of the brake release time);
evaluating a total amount of time the braking mechanism has been released (¶86 – S580 detects if the timer has been exceeded, therefore evaluating the total amount of time the braking mechanism has been released);
determining, after the releasing and the evaluating, if the total amount of time is less than the portion of the brake release duration, whether a distance the autonomous vehicle has moved is within the threshold distance, wherein the distance is compared with an absolute value of a difference between the distance and the adjustment distance (¶86, ¶115-116, and Fig. 5A – when the timer is exceeded corresponding to the recited total amount of time is less than the portion of time, a determination of whether the auto-dock routine indicates target contact which is calculated by comparing the connection distance to the closing distance corresponding to the recited absolute value of a difference between the distance and the adjustment distance within a threshold distance);
repeating the releasing, the evaluating, and the determining if the distance is not within the threshold distance (¶115 – repeated braking requests are calculated based on the vehicle speed proportional to the remaining distance);
applying the braking mechanism, if the total amount of time is not less than the portion of the brake release duration, for another portion of the brake release duration (¶86-88, ¶130, and Figs. 5A and 6D – if the timer is not exceeded, speed changes are iteratively calculated by applying a sloped release of the brakes while moving towards the touch point); and
repeating the determining until (i) the distance is within the threshold distance or (ii) the number of incremental adjustments exceeds five adjustments (¶77-78, ¶86-88, ¶130, and Figs. 5A and 6D – iterative speed adjustments are made utilizing brake releases until the distance is within a threshold distance to the target. The “or” claim element only requires one of the grouping to be disclosed to teach the entirety of the claim as written).
Regarding claim 11, Dodd further discloses wherein when the autonomous vehicle is within the threshold distance a container is automatically loaded or unloaded onto the autonomous vehicle without manual intervention (¶70-71 – autonomous coupling or decoupling of a trailer corresponding to the recited when the autonomous vehicle is within the threshold distance a container is automatically loaded or unloaded onto the autonomous vehicle without manual intervention).
Regarding claims 12 and 19, Dodd further discloses wherein when the autonomous vehicle is within the threshold distance a container is automatically loaded or unloaded onto the autonomous vehicle without manual intervention (¶70-71 – autonomous coupling or decoupling of a trailer corresponding to the recited when the autonomous vehicle is within the threshold distance a container is automatically loaded or unloaded onto the autonomous vehicle without manual intervention) and
wherein when the number of adjustments exceeds the adjustment maximum, an alarm is triggered to facilitate human-aided manual loading or unloading of a container onto the autonomous vehicle (¶86 – when the timer is exceeded due to, for example, the vehicle encountering an obstacle, a tone or other audible notice or visual indicator is initiated corresponding to the recited alarm is triggered to request user input to account for the obstacle corresponding to the recited facilitate human aided manual loading or unloading of the container onto the autonomous vehicle).
While the threshold for human intervention of Dodd uses a timer instead of a number of adjustments, it is well known that iterative feedback adjustments are made using repetitive cycles which generally include a specific cycle time. It would have been obvious to one of ordinary skill in the art before the filing date to derive a maximum number of adjustments utilizing cycle processing times from a time limit resulting in a number of adjustments maximum in order to get the vehicle to the target position without taking “too much time” or contacting it “harshly enough” to cause operator dissatisfaction or loss of quality of the function (Dodd - ¶7).
Claims 4, 5, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Dodd et al. (US 2019/0039425) in view of Uraki (US 2021/0094580), as applied to claims 1, 3, and 13 above, further in view of Parchami et al. (US 2020/0232799).
Regarding claims 4, 5, and 15, Dodd further discloses wherein the plurality of data points comprise a plurality of light and detection ranging (LiDAR) data points and wherein the external reference point is identified using the external reference point detection module by (¶155 - In camera, LIDAR, VORAD or other systems, determining the points and distances does not require cross-talk to establish communications, rather the camera, laser or radar devices on the vehicle V1, V1TG1 establish that they have found an indicator on the target TG2 that sets the points D1, D2, such as a visual indicator, reflector, or other known detectable mechanism):
identifying a subset of the plurality of LiDAR data points located within a designated region (¶155 – identifying reflector position corresponding to the recited identifying a subset of the plurality of LiDAR points located within a designated region);
determining whether the subset is greater than a threshold data point value (¶155 – reflector has a higher reflectivity than other surrounding points corresponding to the recited determination of the subset being greater than a threshold value);
based on the subset being greater than the threshold data point value, generating the plurality of clusters among the subset based on distances between each LiDAR data point (¶155 – LiDAR identifying objects and designating specific objects as reflector position inherently identifies different subsets of points as clusters); and
for each cluster of the plurality of clusters, determining a distance to an internal reference point on the autonomous vehicle (¶155-156 and Fig. 9C – each reflector point D1 and D2, exemplary, is used to determine distances, T1D1 and T2D2, to internal reference points, T1 and T2);
wherein the cluster of the plurality of clusters has a shortest distance in the first axis to the internal reference point, wherein the cluster is identified having the shortest distance in the first axis and a shortest distance to the internal reference point in a second axis (¶144-147, ¶155-156, and Fig. 9C – each cluster, D1 and D2, is identified with a distance, T1D1 and T2D2, to the internal reference points, T1 and T2, which is the shortest distance between the two points which can be measured as a vector of longitudinal pairs corresponding to the recited shortest distance in a first and second axis).
While Dodd does disclose identifying visual indicators based on reflectivity, it does not explicitly disclose utilizing a threshold quantity of data points to make this determination.
However, Parchami discloses an object detection system including the threshold data point value identifying a quantity of data points based on the external reference point (¶58 - “reflections less than a threshold” means a number of reflections from points in a specified volume, e.g., a volume with a height of 1 m and a rectangular bottom surface of 20×20 centimeter (cm) on the ground surface. For example, the threshold may be 20 reflections from points within a volume of 20 cm×20 cm×1 m)
The combination of the reflector position detector of Dodd in view of Uraki with the reflection point quantity threshold of Parchami fully discloses the elements as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the reflector position detector of Dodd in view of Uraki with the reflection point quantity threshold of Parchami in order to accurately determine that the region represents a physical object (Parchami - ¶57).
Claims 10 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Dodd et al. (US 2019/0039425) in view of Uraki (US 2021/0094580), as applied to claims 1 and 13 above, further in view of Li et al. (US 2021/0327271).
Regarding claims 10 and 18, Dodd further discloses wherein the autonomous vehicle is an autonomous prime mover (¶51 – autonomous control of the vehicle for loading/unloading trailers at docks corresponding to the recited autonomous prime mover) and
While Dodd does disclose an autonomous trailer loading/unloading including utilizing sensors mounted on the dock (¶116) it does not explicitly disclose the utilization of an automatic rail mounted gantry.
However, Li explicitly discloses the process of using a Lidar sensors for detecting positioning of a truck/gantry parking system including the external data source is an automatic rail mounted gantry (¶192 and ¶207 – LiDAR and the main controller can be on a connecting beam of the shore crane which automatically detects positioning information and transmits controls to the moving truck corresponding to the recited automatic rail mounted gantry)
The combination of the autonomous docking system of Dodd in view of Uraki with the external data source as an automatic rail mounted gantry of Li fully discloses the invention as claimed.
It would have been obvious to one of ordinary skill in the art before the filing date to have combined the autonomous docking system of Dodd in view of Uraki with the external data source as an automatic rail mounted gantry of Li in order to determine the positioning of the vehicle relative to the crane regardless of the movements of the crane itself (Li - ¶207).
Additional References Cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jeong et al. (US 2023/0194721) discloses a vehicle lidar system and object detecting method including generating an overhead cluster corresponding to an object whose height from the ground may be equal to or larger than a reference height and a grounded cluster whose height from the ground may be smaller than the reference height, in point cloud data obtained by sensing an object; and comparing point data included in the overhead cluster and point data included in the grounded cluster, and removing the grounded cluster upon determining that an object corresponding to the corresponding grounded cluster does not exist. (Abstract)
Peter et al. (US 12,449,548) discloses a method for utilizing clusters of point cloud data generated utilizing a lidar sensor to determine the distance of the cluster from the Lidar sensor (Abstract).
Conclusion
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/MATTHEW J. REDA/Primary Examiner, Art Unit 3665
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