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 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.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
-- “detection module configured to perform target detection …”, in claims 12, 14, and 15;
-- “an area dividing module configured to perform target detection …”, in claims 17, and 18.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim 1 is rejected under 35 U.S.C. 103 as being unpatentable over Yamamoto et al, (US-Patent 11,554,792) in view of Kapusta, (US-PGPUB 20180306905)
Regarding claim 1, Yamamoto discloses a target detection method based on
laser scanning, comprising:
scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle; and performing target detection on the first point cloud, (see at least: Fig. 5, steps S1-S2, col. 16, lines 44 through col. 17, line 20, the LiDAR control module 430a determines whether a target object (for example, a pedestrian or another vehicle) exists in a surrounding area of the vehicle 1. The LiDAR unit 44a scans a laser beam at a predetermined angular pitch Δθ in the horizontal direction of the vehicle 1 and at a predetermined angular pitch Δφ in the up-and-down direction of the vehicle 1, and if the result of the determination made in step S1 is YES, the LiDAR control module 430a executes an operation in step S2, [i.e., scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle, “implicit by scanning a laser beam at a predetermined angular pitch Δθ in the horizontal direction as well as in the up-and-down direction of the vehicle 1”; and performing target detection on the first point cloud, “determining whether a target object) exists in a surrounding area of the vehicle 1, and if the result of the determination made in step S1 is (YES), implicitly detecting the target object”);
when a target is detected, determining a fine scanning area and an observation scanning area based on the target, the fine scanning area corresponding to a position of the target in the preset scanning area, and the observation scanning area being an area in the preset scanning area except the fine scanning area, (see at least: Fig. 5, step S3, and col. 17, lines 21-49, the LiDAR control module 430a identifies a position of the pedestrian P (the target object) based on the point group data (step S3). The LiDAR control module 430a determines an angular area (Sx) (an example of a first angular area) based on the information on the position of the pedestrian P. Further, as shown in FIG. 6, since the pedestrian P exists within the detection area S2 of the LiDAR unit 44a, the attribute of the target object becomes a pedestrian, [i.e., when a target is detected, determining a fine scanning area, “determines an angular area (Sx) “ and an observation scanning area based on the target, “implicitly detecting an area S2 “, based on the target, “the pedestrian P”. The fine scanning area corresponding to a position of the target in the preset scanning area, “see Fig. 7, where the area Sx, represent the position of the target object P”, and the observation scanning area being an area in the preset scanning area except the fine scanning area, “see Figs. 6-7, where the area S2 corresponds to the preset scanning area except the fine scanning area”]); and
scanning the fine scanning area with a second scanning resolution a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx (refer to FIG. 7) where the pedestrian P (the target object) exists, [i.e., scanning the fine scanning area to obtain a second point cloud in a second scanning cycle, “implicit by 430a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx”]), wherein the second scanning resolution is greater than the first scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution, (see at least: col. 18, lines 4-15, the space resolution in the angular area Sx is higher than space resolutions in other areas than the angular area Sx in the detection area S2, as result, the information on the target object (the pedestrian P) existing in the angular area Sx, is acquired with accuracy, [i.e., wherein the second scanning resolution is greater than the first scanning resolution, “the space resolution in the angular area Sx is higher than space resolutions in other areas”]).
Yamamoto does not expressly disclose scanning the observation scanning area with a third scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution.
However, Kapusta discloses scanning the observation scanning area with a third scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution, (Abstract, and Fig. 4, Par. 0029, detecting a first object can be identified within the first image by detection circuitry, such as the detection circuitry 124 (step 420), …light beam can be emitted by the scanning laser 108 can be scanned over the first region of interest at a first spatial sampling resolution (step 450). A light beam, such as can be emitted by the scanning laser 108 can be scanned over the field of view outside of the first region of interest at a second spatial sampling resolution, wherein the second sampling resolution can be less than the first spatial sampling resolution (step 460), [i.e., scanning the observation scanning area, “scanning field of view outside the first region”, with a third scanning resolution, “second spatial sampling resolution”, and the third scanning resolution is less than or equal to the first scanning resolution, “the second sampling resolution can be less than the first spatial sampling resolution”]).
Yamamoto and Kapusta are combinable because they are both concerned with object detection. Therefore, it would have been obvious to a person of ordinary skill in the art, to modify Yamamoto, to use step 460, as though by Kapusta, in order to scan the field of view outside of the first region of interest at a second spatial sampling resolution less than the first spatial sampling resolution, to thereby adjusting a field of view in a lidar system, (Kapusta, Par. 0019).
Regarding claim 2, the combination Yamamoto and Kapusta as whole discloses limitations of claim 1.
Yamamoto further discloses wherein when there are multiple targets, the fine scanning area is an area corresponding to multiple positions of the multiple targets in the preset scanning area, (see at least: col. 19, lines 29-33, when a plurality of target objects exist within the detection area S2 of the LiDAR unit 44a, a plurality of angular areas (Sx), each of which is configured to cover at least one of the plurality of target objects, may be provided within the detection area S2, [i.e., the fine scanning area, (area Sx) is an area corresponding to multiple positions of the multiple targets in the preset scanning area, “implicit by a plurality of target objects existing within the detection area S2”]).
Regarding claim 3, the combination Yamamoto and Kapusta as whole discloses limitations of claim 1.
Kapusta further discloses performing target detection on the second point cloud to obtain a second detection result of the target, (see at least: Fig. 2B, where region 236, corresponds to the region of interest where the object is detected within the second point cloud of frame 231).
Regarding claim 4, the combination Yamamoto and Kapusta as whole discloses limitations of claim 1.
Yamamoto further discloses if a new target exists in the second detection result of the second point cloud, determining the new target as the target; and updating the fine scanning area and the observation scanning area based on the target, (see at least: col. 3, lines 41-45, LiDAR control module may be configured to update a position of the target object based on point group data newly acquired from the LiDAR unit and then update the first angular area based on the updated position of the target object, [i.e., if a new target exists in the second detection result of the second point cloud, “when the target object is implicitly detected point group data newly acquired from the LiDAR unit”, determining the new target as the target; “implicit by update a position of the target object”, and updating the fine scanning area and the observation scanning area based on the target, “implicitly by updating the first angular area based on the updated position of the target object).
Regarding claim 8, Yamamoto discloses a target detection method based on
laser scanning, comprising:
scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle; and performing target detection on the first point cloud, (see at least: Fig. 5, steps S1-S2, col. 16, lines 44 through col. 17, line 20, the LiDAR control module 430a determines whether a target object (for example, a pedestrian or another vehicle) exists in a surrounding area of the vehicle 1. The LiDAR unit 44a scans a laser beam at a predetermined angular pitch Δθ in the horizontal direction of the vehicle 1 and at a predetermined angular pitch Δφ in the up-and-down direction of the vehicle 1, and if the result of the determination made in step S1 is YES, the LiDAR control module 430a executes an operation in step S2, [i.e., scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle, “implicit by scanning a laser beam at a predetermined angular pitch Δθ in the horizontal direction as well as in the up-and-down direction of the vehicle 1”; and performing target detection on the first point cloud, “determining whether a target object) exists in a surrounding area of the vehicle 1, and if the result of the determination made in step S1 is (YES), implicitly detecting the target object”);
when a target is detected, determining a fine scanning area and an observation scanning area based on the target, the fine scanning area corresponding to a position of the target in the preset scanning area, and the observation scanning area being an area in the preset scanning area except the fine scanning area, (see at least: Fig. 5, step S3, and col. 17, lines 21-49, the LiDAR control module 430a identifies a position of the pedestrian P (the target object) based on the point group data (step S3). The LiDAR control module 430a determines an angular area (Sx) (an example of a first angular area) based on the information on the position of the pedestrian P. Further, as shown in FIG. 6, since the pedestrian P exists within the detection area S2 of the LiDAR unit 44a, the attribute of the target object becomes a pedestrian, [i.e., when a target is detected, determining a fine scanning area, “determines an angular area (Sx) “ and an observation scanning area based on the target, “implicitly detecting an area S2 “, based on the target, “the pedestrian P”. The fine scanning area corresponding to a position of the target in the preset scanning area, “see Fig. 7, where the area Sx, represent the position of the target object P”, and the observation scanning area being an area in the preset scanning area except the fine scanning area, “see Figs. 6-7, where the area S2 corresponds to the preset scanning area except the fine scanning area”]); and
scanning the fine scanning area with a second scanning resolution a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx (refer to FIG. 7) where the pedestrian P (the target object) exists, [i.e., scanning the fine scanning area to obtain a second point cloud, “implicit by 430a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx”]), wherein the second scanning resolution is greater than the first scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution, (see at least: col. 18, lines 4-15, the space resolution in the angular area Sx is higher than space resolutions in other areas than the angular area Sx in the detection area S2, as result, the information on the target object (the pedestrian P) existing in the angular area Sx, is acquired with accuracy, [i.e., wherein the second scanning resolution is greater than the first scanning resolution, “the space resolution in the angular area Sx is higher than space resolutions in other areas”]).
Yamamoto does not expressly disclose scanning the observation scanning area with a third scanning resolution; wherein a number of point clouds per unit area in the fine scanning area when scanning with the second scanning resolution is larger than a number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution, and a number of point clouds per unit area in the observation scanning area when scanning with the third scanning resolution is smaller than the number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution.
Kapusta discloses scanning the observation scanning area with a third scanning resolution, (Abstract, and Fig. 4, Par. 0029, detecting a first object can be identified within the first image by detection circuitry, such as the detection circuitry 124 (step 420), …light beam can be emitted by the scanning laser 108 can be scanned over the first region of interest at a first spatial sampling resolution (step 450). A light beam, such as can be emitted by the scanning laser 108 can be scanned over the field of view outside of the first region of interest at a second spatial sampling resolution, wherein the second sampling resolution can be less than the first spatial sampling resolution (step 460), [i.e., scanning the observation scanning area, “scanning field of view outside the first region”, with a third scanning resolution, “second spatial sampling resolution”].
Kapusta further discloses wherein a number of point clouds per unit area in the fine scanning area when scanning with the second scanning resolution is larger than a number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution, (see at least: Par. 0017, Fig. 2A, where the first region of interest 235 can include 36 scanned points, and the portion of the frame outside of the region of interest can include 17 scanned points, [i.e., number of point clouds per unit area … when scanning with the second scanning resolution, “where the region of interest 235 include 36 scanned points”, is larger than a number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution, “outside of the region of interest 235 including 17 scanned points”]); and a number of point clouds per unit area in the observation scanning area when scanning with the third scanning resolution is smaller than the number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution, (see at least: Par. 0017, Fig. 2B, where the second region of interest 236 can include 12 scanned points, and the portion of the frame outside of the region of interest can include 23 scanned points, [i.e., a number of point clouds per unit area in the observation scanning area when scanning with the third scanning resolution, “the second region of interest 236 corresponds to the observation scanning area, and second region of interest 236 can include 12 scanned points”, is smaller than the number of point clouds per unit area in the preset scanning area when scanning with the first scanning resolution, “the portion of the frame outside of the region of interest can include 23 scanned points”]).
Yamamoto and Kapusta are combinable because they are both concerned with object detection. Therefore, it would have been obvious to a person of ordinary skill in the art, to modify Yamamoto, where the frame can include scanning patterns of a collection of scanned points, which can be irregularly spaced across a field of view of the optical system, as though by Kapusta, in order to provide a dynamic region of interest in a LIDAR system, (Kapusta, Par. 0001).
Regarding claim 9, the combination Yamamoto and Kapusta as whole discloses limitations of claim 8.
Yamamoto further discloses wherein the fine scanning area comprises a corresponding area of each target in the preset scanning area, (see at least: Fig. 5, 7, step S4, col. 17, lines 35-37, in step S4, the LiDAR control module 430a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx “fine scanning area”, where the pedestrian P (the target object) exists)).
Regarding claim 10, the combination Yamamoto and Kapusta as whole discloses limitations of claim 8.
Yamamoto further discloses determining whether a state of the target changes according to the second point cloud, the state of the target comprising at least one of a number, a speed, an azimuth angle, or a distance of the target; and when the state of the target changes, (see at least: col. 18, lines 16-36, the LiDAR control module 430a determines whether the attribute of the target object can be identified based on the point group data newly acquired from the LiDAR unit 44a (step S5); and from col. 17, lines 28-31, the LiDAR control module 430a may identify information on a distance between the vehicle 1 and the pedestrian P and information on an angle of the pedestrian P with respect to the vehicle 1, [i.e., determining whether a state of the target changes according to the second point cloud, “implicit by determining determines whether the attribute of the target object can be identified”, the state of the target comprising at least one of a number, a speed, an azimuth angle, or a distance of the target; and when the state of the target changes, “implicit by identifying information on a distance between the vehicle 1 and the pedestrian P”]); and
updating the fine scanning area and the observation scanning area based on the target determined in the second point cloud, (co. 18, lines 32-36, the LiDAR control module 430a at first updates foe angular area Sx based on the updated information on the position of the pedestrian P and then increases further the scanning resolution of the LiDAR unit 44a only in the angular area Sx, [i.e., updating the fine scanning area and the observation scanning area, (implicit by updating the angular area Sx) based on the target determined in the second point cloud, “the attribute of the target object determined in the newly acquired point group data”]).
Regarding claim 12, claim 12 recites substantially similar limitations as set forth in claim 1. As such, claim 12 is rejected for at least similar rational.
The Examiner further acknowledged the following additional limitation(s): “A target detection device based on laser scanning”. However, Yamamoto discloses the “target detection device based on laser scanning”, (see at least: co. 8, lines 25-32, “the vehicle control unit 3”).
Regarding claim 13, claim 13 recites substantially similar limitations as set forth in claim 2. As such, claim 13 is rejected for at least similar rational.
Regarding claim 14, claim 14 recites substantially similar limitations as set forth in claim 4. As such, claim 14 is rejected for at least similar rational.
Regarding claim 17, claim 17 recites substantially similar limitations as set forth in claim 8. As such, claim 17 is rejected for at least similar rational.
The Examiner further acknowledged the following additional limitation(s): ““A target detection device based on laser scanning”. However, Yamamoto discloses the “target detection device based on laser scanning”, (see at least: co. 8, lines 25-32, “the vehicle control unit 3”).
Regarding claim 18, claim 18 recites substantially similar limitations as set forth in claim 10. As such, claim 18 is rejected for at least similar rational.
Regarding claim 20, claim 20 recites substantially similar limitations as set forth in claim 9. As such, claim 20 is rejected for at least similar rational.
Claims 5, 7, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Yamamoto and Kapusta, as applied to claim 4 above; and further in view of Pelz, (US-PGPUB 20200041618)
Regarding claim 5, the combination Yamamoto and Kapusta as whole discloses limitations of claim 4.
The combination Yamamoto and Kapusta as whole does not expressly disclose, that if no new target exists in the second detection result of the second point cloud, scanning the preset scanning area with the first scanning resolution in at least one scanning cycle until the target is detected.
However, Pelz discloses if no new target exists in the second detection result of the second point cloud, scanning the preset scanning area with the first scanning resolution in at least one scanning cycle until the target is detected, (see at least: Fig. 4, Par. 0045, controller 106 continues with the first-resolution scan until an object is detected (Block 302). The analysis unit 114 may confirm the presence of an object, based on the output of the photosensor 110, [i.e., if no new target exists in the second detection result of the second point cloud, “Fig. 4, (Block 302): object detected –(No)”, scanning the preset scanning area with the first scanning resolution in at least one scanning cycle until the target is detected, “continues with the first-resolution scan until an object is detected”).
Yamamoto, Kapusta, and Pelz are combinable because they are all concerned with object detection. Therefore, it would have been obvious to a person of ordinary skill in the art, to modify the combination Yamamoto and Kapusta, to use controller 106, as though by Pelz, in order to scan the preset scanning area with the first scanning resolution in at least one scanning cycle until the target is detected, (Pelz, Par. 0045).
Regarding claim 7, the combination Yamamoto and Kapusta as whole discloses limitations of claim 1.
The combination Yamamoto and Kapusta as whole does not expressly disclose, wherein after performing the target detection on the first point cloud of the first scanning cycle, the method further comprises: if no target is detected in a first detection result of the first point cloud, scanning the preset scanning area with the first scanning resolution to obtain a corresponding updated first point cloud, until a target is detected in the first detection result of the first point cloud.
However, Pelz discloses that if no target is detected in a first detection result of the first point cloud, scanning the preset scanning area with the first scanning resolution to obtain a corresponding updated first point cloud, until a target is detected in the first detection result of the first point cloud, (see at least: Fig. 4, Par. 0045, controller 106 continues with the first-resolution scan until an object is detected (Block 302). The analysis unit 114 may confirm the presence of an object, based on the output of the photosensor 110, [i.e., if no target is detected in a first detection result of the first point cloud, “Fig. 4, (Block 302): object detected –(No)”, scanning the preset scanning area with the first scanning resolution to obtain a corresponding updated first point cloud, until a target is detected in the first detection result of the first point cloud, “continues with the first-resolution scan until an object is detected”).
Yamamoto, Kapusta, and Pelz are combinable because they are all concerned with object detection. Therefore, it would have been obvious to a person of ordinary skill in the art, to modify the combination Yamamoto and Kapusta, to use controller 106, as though by Pelz, in order to scan the preset scanning area with the first scanning resolution in at least one scanning cycle until the target is detected, (Pelz, Par. 0045).
Regarding claim 15, claim 15 recites substantially similar limitations as set forth in claim 5. As such, claim 15 is rejected for at least similar rational.
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Yamamoto and Kapusta, as applied to claim 4 above; and further in view of Hicks, (US-Patent 10,345,447)
Regarding claim 6, the combination Yamamoto and Kapusta as whole discloses limitations of claim 1.
Yamamoto further discloses scanning the fine scanning area with a second scanning resolution
In the other hand, Kapusta discloses scanning the observation scanning area with a third scanning resolution, (Kapusta, Abstract, and Fig. 4, Par. 0029, “see the rejection of claim 1 for more details”)
However, the combination Yamamoto and Kapusta as whole does not expressly disclose reducing a frame rate to obtain the second scanning resolution, and increasing the frame rate to obtain the third scanning resolution.
Hicks discloses reducing a frame rate to obtain the second scanning resolution and increasing the frame rate to obtain the third scanning resolution, (see at least: col. 8, line 62 through col. 9, line 20, ROI scan may be adjusted by increasing the density of the scan lines. In order to increase the frame rate of normal scans, the lidar may scan fewer than all of the lines. The ROI scan can then allow for the ROI to be scanned at the full possible resolution or at a higher resolution, and in other cases, the ROI scan may be adjusted by decreasing the scanning rate, a slower speed scan also allows more detail to be observed, [i.e., implicitly reducing a frame rate, “implicit by decreasing the scanning rate”, to obtain the second scanning resolution, “higher resolution”; and increasing the frame rate to obtain the third scanning resolution, “explicitly increasing the frame rate to obtain higher resolution, “third scanning resolution higher than predetermined resolution”]).
Yamamoto, Kapusta, and Hicks are combinable because they are all concerned with object detection. Therefore, it would have been obvious to a person of ordinary skill in the art, to modify the combination Yamamoto and Kapusta, to adjust the ROI scan, as though by Hicks, in order to allow more detail to be observed, (Hicks, col. 9, lines 5-7).
Regarding claim 16, claim 16 recites substantially similar limitations as set forth in claim 6. As such, claim 16 is rejected for at least similar rational.
Allowable Subject Matter
Claims 11 and 19 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
With respect to claim 11, the prior art of record, alone or in reasonable combination, does not teach or suggest, the following limitation(s), (in consideration of the claim as a whole):
“when the distance of the target is greater than or equal to a set safety distance, reducing a frame rate, increasing a scanning resolution of the fine scanning area, and reducing a scanning resolution of the observation scanning area; and when the distance of the target is less than the set safety distance, and the speed of the target which is gradually approaching is greater than a preset speed, increasing the frame rate, increasing the scanning resolution of the fine scanning area, and reducing the scanning resolution of the observation scanning area”.
The relevant prior art of record, Yamamoto et al, (US-Patent 11,554,792) discloses a target detection method based on laser scanning, comprising:
scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle; and performing target detection on the first point cloud, (see at least: Fig. 5, steps S1-S2, col. 16, lines 44 through col. 17, line 20, the LiDAR control module 430a determines whether a target object (for example, a pedestrian or another vehicle) exists in a surrounding area of the vehicle 1. The LiDAR unit 44a scans a laser beam at a predetermined angular pitch Δθ in the horizontal direction of the vehicle 1 and at a predetermined angular pitch Δφ in the up-and-down direction of the vehicle 1, and if the result of the determination made in step S1 is YES, the LiDAR control module 430a executes an operation in step S2, [i.e., scanning a preset scanning area with a first scanning resolution to obtain a first point cloud in a first scanning cycle, “implicit by scanning a laser beam at a predetermined angular pitch Δθ in the horizontal direction as well as in the up-and-down direction of the vehicle 1”; and performing target detection on the first point cloud, “determining whether a target object) exists in a surrounding area of the vehicle 1, and if the result of the determination made in step S1 is (YES), implicitly detecting the target object”);
when a target is detected, determining a fine scanning area and an observation scanning area based on the target, the fine scanning area corresponding to a position of the target in the preset scanning area, and the observation scanning area being an area in the preset scanning area except the fine scanning area, (see at least: Fig. 5, step S3, and col. 17, lines 21-49, the LiDAR control module 430a identifies a position of the pedestrian P (the target object) based on the point group data (step S3). The LiDAR control module 430a determines an angular area (Sx) (an example of a first angular area) based on the information on the position of the pedestrian P. Further, as shown in FIG. 6, since the pedestrian P exists within the detection area S2 of the LiDAR unit 44a, the attribute of the target object becomes a pedestrian, [i.e., when a target is detected, determining a fine scanning area, “determines an angular area (Sx) “ and an observation scanning area based on the target, “implicitly detecting an area S2 “, based on the target, “the pedestrian P”. The fine scanning area corresponding to a position of the target in the preset scanning area, “see Fig. 7, where the area Sx, represent the position of the target object P”, and the observation scanning area being an area in the preset scanning area except the fine scanning area, “see Figs. 6-7, where the area S2 corresponds to the preset scanning area except the fine scanning area”]); and
scanning the fine scanning area with a second scanning resolution a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx (refer to FIG. 7) where the pedestrian P (the target object) exists, [i.e., scanning the fine scanning area to obtain a second point cloud in a second scanning cycle, “implicit by 430a increases the scanning resolution of the LiDAR unit 44a only in an angular area Sx”]), wherein the second scanning resolution is greater than the first scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution, (see at least: col. 18, lines 4-15, the space resolution in the angular area Sx is higher than space resolutions in other areas than the angular area Sx in the detection area S2, as result, the information on the target object (the pedestrian P) existing in the angular area Sx, is acquired with accuracy, [i.e., wherein the second scanning resolution is greater than the first scanning resolution, “the space resolution in the angular area Sx is higher than space resolutions in other areas”]).
However, Yamamoto fails to teach or suggest, either alone or in combination with the other cited references, when the distance of the target is greater than or equal to a set safety distance, reducing a frame rate, increasing a scanning resolution of the fine scanning area, and reducing a scanning resolution of the observation scanning area; and when the distance of the target is less than the set safety distance, and the speed of the target which is gradually approaching is greater than a preset speed, increasing the frame rate, increasing the scanning resolution of the fine scanning area, and reducing the scanning resolution of the observation scanning area.
A further prior art of record, Kapusta, (US-PGPUB 20180306905) discloses scanning the observation scanning area with a third scanning resolution, and the third scanning resolution is less than or equal to the first scanning resolution, (Abstract, and Fig. 4, Par. 0029, detecting a first object can be identified within the first image by detection circuitry, such as the detection circuitry 124 (step 420), …light beam can be emitted by the scanning laser 108 can be scanned over the first region of interest at a first spatial sampling resolution (step 450). A light beam, such as can be emitted by the scanning laser 108 can be scanned over the field of view outside of the first region of interest at a second spatial sampling resolution, wherein the second sampling resolution can be less than the first spatial sampling resolution (step 460), [i.e., scanning the observation scanning area, “scanning field of view outside the first region”, with a third scanning resolution, “second spatial sampling resolution”, and the third scanning resolution is less than or equal to the first scanning resolution, “the second sampling resolution can be less than the first spatial sampling resolution”]).
However, Kapusta fails to teach or suggest, either alone or in combination with the other cited references, when the distance of the target is greater than or equal to a set safety distance, reducing a frame rate, increasing a scanning resolution of the fine scanning area, and reducing a scanning resolution of the observation scanning area; and when the distance of the target is less than the set safety distance, and the speed of the target which is gradually approaching is greater than a preset speed, increasing the frame rate, increasing the scanning resolution of the fine scanning area, and reducing the scanning resolution of the observation scanning area.
Another prior art of record, Hicks, (US-Patent 10,345,447) discloses that the lidar may scan fewer than all of the lines in order to increase the frame rate of normal scans, and the ROI scan can then allow for the ROI to be scanned at the full possible resolution or at a higher resolution, and in other cases, the ROI scan may be adjusted by decreasing the scanning rate, where a slower speed scan also allows more detail to be observed, (col. 8, line 62 through col. 9, line 20); but fails to teach or suggest, either alone or in combination with the other cited references, the above limitations (as combined with the other claimed limitations).
Regarding claim 19, claim 19 recites substantially similar limitations as set forth in claim 11. As such, claim 19 is in condition for allowance, for at least similar reasons, as stated above.
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/AMARA ABDI/Primary Examiner, Art Unit 2668 08/26/2026
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