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 .
This communication is responsive to the Application No. 18/724,029 filled on 01/23/2026.
Election/Restrictions
Applicant's election without traverse of Group III, Claims 4-8 and 13-14, in the reply filed on 01/23/2026. However, upon further review of the claimed invention in three different species, the search and examination of all the claims in the application can be (or has been) made without serious burden, therefore, the examiner examined them on the merits (MPEP 803). For the above reasons, the restriction has been withdrawn.
Claim Objections
Claims 4-10 and 13-14 are objected to because of the following informalities:
Claim 4 is a method claim and depends on a picking robot claim 1. Claim 4 should apparently be written in independent form including all the limitation of claim 1. Appropriate correction is required.
Regarding claim 4, the phrase “each fruit tree image” on line 6 should apparently be “each of the fruit tree images”, and “each fruit tree image” on line 8-10 should apparently be “the each of the fruit tree images”. Claims 5-8 and 13-14 are objected for the same reasons as discussed above with respect to claim 4. Appropriate correction is required.
Claim 9 is an electronic device claim and depends directly or indirectly upon picking robot claim 1 and method claim 4. Claim 9 should be written in independent form including all the limitations of claims 1 and 4.
Claim 10 is a non-transitory computer-readable storage medium claim and depends directly or indirectly upon picking robot claim 1 and method claim 4. Claim 10 should be written in independent form including all the limitations of claims 1 and 4.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7 and 9-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 cites “partial fruit positioning distribution information” on line 13, where the phrase “partial” is a relative term and renders the claim indefinite. The term is not defined by the claim, the specification doesn’t provide a standard for ascertaining the requisite degree, and one of the ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Furthermore, the specification fails to further define what the partial fruit positioning distribution information is. Therefor the claim is indefinite.
Claims 2-7 and 9-20 are also rejected by the virtue of their dependency on rejected base claim(s).
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-7 and 9-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1 cites " partial fruit positioning distribution information", wherein the particulars for the phrase “partial fruit position distribution information” is not being specifically described within the specification. Therefore, claim 1 do not satisfy the written description requirement.
Claims 2-7 and 9-20 are also rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, by virtue of their dependency on the base claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Analysis (Claim 8)
Step 1: Statutory Category-Yes
The claim 8 is directed to "A positioning method”. Therefore, the claim 8 is within at least one of the four statutory categories.
Step 2A-Prong 1: Judicially Exception Recited-Yes
Regarding Prong I of the Step 2A analysis in 2019 PEG, claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
The claim 4 recites the limitations of: A fruit positioning apparatus, comprising: an output module, configured to obtain fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules, and
input the fruit tree images into a predefined target detection model to obtain two-dimensional bounding box information and a mask area of each fruit in each fruit tree image output by the predefined target detection model; a positioning module, configured to generate a three-dimensional point cloud of each fruit in each fruit tree image by using the mask area of each fruit in each fruit tree image and corresponding image depth information, and determine a first positioning coordinate point of each fruit in each fruit tree image based on the three-dimensional point cloud and the two-dimensional bounding box information of each fruit in each fruit tree image; and a processing module, configured to determine global fruit positioning distribution information of the operation area based on a result obtained by transforming the first positioning coordinate point of each fruit in each fruit tree image to base coordinate system. The highlighted elements above are considered to be directed to mental processes and/or mathematical concepts, such as, inputting the fruit tree images to obtain two-dimensional bounding box information and a mask area of each fruit in each fruit tree image output, encompasses mathematical calculation based on captured image data, and/or it could be done by pen and paper based on captured images; generate a three-dimensional point cloud of each fruit in each fruit tree image by using the mask area of each fruit in each fruit tree image and corresponding image depth information, also could be done by pen and paper; determine a first positioning coordinate point of each fruit in each fruit tree image based on the three-dimensional point cloud and the two-dimensional bounding box information of each fruit in each fruit tree image; and determine global fruit positioning distribution information of the operation area based on a result obtained by transforming the first positioning coordinate point of each fruit in each fruit tree image to base coordinate system, encompasses a mental process. Therefore, the highlighted limitation above, as drafted, is a simple process that, under its broadest reasonable interpretation, covers performance of the limitation in mental process and/or mathematical calculation but for the recitation of the underlined limitations above, where the underline limitations are referred to obtain images, captured by first image collection modules [i.e., a color depth camera/ stereo vision camera], and display image by a output module [i.e., display] is insignificant extra solution activity. The other additional elements the predefined target detection model and a positioning module constitutes a generic computer to process captured image to generate each fruit position, no more than mere instructions to apply the exception using a computer, and is insignificant.
Step 2A—Prong 2: Integrated into a Practical Application-No
The claim recites additional elements, such as, “output module to obtaining the fruit tree images of the respective sub-areas in the operation area that are collected by the respective first image collection modules, is simply captured images by a camera and obtained image from a color depth camera/ stereo vision camera, is insignificant extra solution activity. The other additional elements, such as “a predefined target detection model” to obtain two-dimensional bounding box information and a mask area of each fruit in each fruit tree image, no more than mere instructions to apply the exception using a computer to process captured image by a color depth camera/ stereo vision camera and obtain boundary box information of each fruit in the fruit tree images. The other additional element “positioning module” to generate a three-dimensional point cloud of each fruit in each fruit tree image is also no more than mere instructions to apply the exception using a computer to process captured image by a color depth camera/ stereo vision camera to generate position information of the fruit. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does do not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
Step 2B: Claim provides an Inventive Concept-No
Claims 8 is evaluated as to whether the claims as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim.
As discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than insignificant extra-solution activity. Under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. Here, obtaining the fruit tree images of the respective sub-areas in the operation area that are collected by the respective first image collection modules (i.e., color depth camera/ stereo vision camera) is a well‐understood, routine, and conventional function. See MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015). Accordingly, a conclusion that the capturing image by (first image collection module( i.e., a color depth camera/ stereo vision camera), and process captured images to obtain two-dimensional boundary box information [i.e., fruit position information], is conventional activity, supported under Berkheimer. The other additional element, “output module”, “position module”, “target detection module” is recited as high level of generality and merely automates the generate and determine steps, therefore acting as a generic computer to perform the abstract idea, doesn’t use the judicial exception in a manner that impose a meaningful limit on the judicial exception, such that the claim is more than drafting effort designed to monopolize the exception. This additional limitation is no more than mere instruction to apply the exception using a computer. The claim The claim 8 is ineligible.
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: “first image collection module” in claims 1, 4, 8; “second image collection module” in claim 1; “predetermined target detection model” in claims 4, 8; “output module” in claim 8; “positioning module” and “processing module” in claim 8; have has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because they use a generic placeholder “means for” coupled with functional language without reciting sufficient structure to achieve the function.
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. Specification, Para. [0037]-[0039], cites “Any one of the fruit positioning methods described above is implemented when the computer program is executed by a processor. A processor uniformly transforms images collected from various visual angles to base coordinates of the robot, synchronously obtains visual information of all picking targets in an operation area, and generates global fruit positioning distribution information that matches dimensions of an operation space range of the robot, which facilitates efficient collaborative operation of various robotic arms, can achieve accurate fruit detection at a close distance in the operation area, obtain fruit information in a wide range, and improve the accuracy and range of fruit positioning, and is conductive to greatly improving the fruit picking efficiency of the robot.” Therefore, the claimed “predefined target detection model” is construed as a computer. Additionally, in para. [0096], cites “the predefined target detection model may be constructed based on a deep convolutional neural network model”. In the specification, in para. [0054], cites “the image collection modules may specifically use color depth cameras based on different ranging principles, for example, various types of color depth cameras (which may also be referred to as stereo vision cameras) based on a structured light technology, a binocular stereo vision matching technology, or flight time, and are configured to obtain a fruit tree image in the operation area”, and in [0077] cites “the fruit tree images collected by the plurality of first image collection modules (such as stereo vision cameras) are observed.”. Therefore, “first image collection module is interpreted as ”camera’. Further, a review of the original specification, filed on 06/25/2024, Para. [0075], cites “The processor may obtain fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules, obtain the base coordinate system, and calibrate coordinates of the fruit tree images collected by the first image collection modules, and uniformly transform each fruit tree image to the base coordinate system for representing”. Therefore, output module is interpreted as processor. Specification, in para. [0083], discloses “each first image collection module may transmit collected fruit images, by means of communication manners such as wired connection, Wireless Fidelity (WIFI) or a 4th Generation Mobile Communication Technology (4G)/a 5th Generation Mobile Communication Technology (5G), to an image processing module with a built-in processor, such as a graphic edge computing chip, a graphic workstation, and a graphic server, which completes recognition and positioning of a fruit target through a series of algorithms such as machine learning-based image recognition, detection, and segmentation”. Therefore, the claimed processing module is interpreted as hardware with built-in processor.
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.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 8 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim elements “positioning module” in claim 8; are limitations that invokes 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the corresponding entire claimed function and to clearly link the structure, material or acts to the function. The specification does not provide sufficient details such as one of ordinary skills in the art would understand which structures perform(s) the corresponding claim function in claim 8.
Therefore, the claim 8 is indefinite and are rejected under 35 U.S.C. 112(b).
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 8 is rejected under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
As described above from the 112(f) interpretation and 112 (b) rejection, the disclosure does not provide adequate structure for “positioning module” to perform the corresponding claimed function in claim 8. The specification does not demonstrate that applicant has made an invention that achieves the claimed function because the invention is not described with sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor had possession of the claimed invention.
Therefore, the claim 8 is rejected under 35 U.S.C. 112(a), as failing to comply with the written description requirement.
Examiner's Note
Examiner has cited particular paragraphs/ columns and line numbers or figures in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, in preparing the responses, to fully consider the references in entirety as potentially teaching
all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. Applicant is reminded that the Examiner is entitled to give the broadest reasonable interpretation to the language of the claims. Furthermore, the Examiner is not limited to Applicants' definition which is not specifically set forth in the claims.
Claim Objections (having allowable subject matter)
Claims 1-7 and 9-20 would be allowable if written to overcome the rejection(s) under 35 U.S.C. 112(b), 35 U.S.C. 112 (a), and claims objections for informalities, set forth in this Office action.
Claim 8 would be allowable if written to overcome the rejection(s) under 35 U.S.C. 112(b), 35 U.S.C. 112 (a), 35 U.S.C. 101, and claims objections for informalities, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 1, the closest prior art, Lu et al. (IUS 2025/0081892 A1) teaches a picking robot (See 1 and/or Fig. 9, and/or Abstract, Para. [0017], [0034], discloses “robotic harvester for picking fruit”), comprising:
a robot body, wherein the robot body comprises a processor (See Fig. 1, discloses “a robot body and processor”);
a plurality of first image collection modules and one second image collection module are mounted on the robot body (See Para. [0037]-[0038], discloses “RGB 20 and RGB-D 12 cameras”);
the robot body comprises a plurality of robotic arms (See Fig. 9, Para. [0050], discloses “two separate robotic manipulation arms”);
wherein
each robotic arm has one corresponding first image collection module mounted nearby (See at least Fig. 3, Para. [0043]-[0044], [0050], discloses “RGB-D camera 12 and RGB camera 20”); each first image collection module does not interfere with a corresponding robotic arm (See Fig. 2-3, camera 20 and 12, i.e., image collection modules doesn’t interfere each other”, and See Para. [0038]-[0039], “the RGB camera 20 is installed he RGB-D camera is positioned above the manipulation arm, and the RGB-D camera 12 is mounted on a horizontal frame 14”. The examiner notes that the cited reference teaches two cameras is positioned above the manipulation arm and horizontal frame, but it doesn’t explicitly say that each of the camera are mounted on robotic arms. However, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to have modified the teaching of Lu with mounting each of the cameras on the robotic arms in order to move camera with arms movement and then use image information to locate fruit location in respect to the robotic arms);
the second image collection module is mounted at a position of a base of the robot body for determining base coordinate system (See Para. [0038]-[0039], “the RGB camera 20 is installed he RGB-D camera is positioned above the manipulation arm, and the RGB-D camera 12 is mounted on a horizontal frame 14”. The examiner notes that the cited reference teaches two cameras, but none of the cameras is mounted on a base of the robot body. However, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the application, to have modified the teaching of Lu with mounding one of the cameras on base of the robot body in order to capture image of wider view of the environment”); and
the processor is configured to: determine, based on fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules and the base coordinate system, fruit positioning of the operation area (See Para. [0043], “The acquired RGB-D image data is first processed using a specially developed deep learning algorithm to identify all fruits 26 in the workspace, using “bounding boxes”, as described in the fruit detection flow chart FIG. 5 and in FIG. 7. The rough localization information for all detected fruits 26 in the robot's working space is subsequently obtained by fusing the bounding boxes with the point cloud data (depth image) provided by the RGB-D camera 12”, and see Para. [0049], “The controller/processor uses the images and a laser triangulation technique to localize the fruit and to determine the xyz position of the centroid of the target fruit”), and
determine partial fruit positioning corresponding to each robotic arm according to the global fruit positioning distribution information, to control the robotic arms to perform operation (See Para. [0035], “the perception system is activated to detect and localize the fruits (preferably apples) within the robotic manipulation arm's workspace, a planning algorithm is used to generate a reference trajectory, and the controller/processor actuates the manipulation arm to follow the reference trajectory to approach the target fruit. After successfully attaching the fruit to the end effector, a rotation mechanism in the manipulation arm is triggered to rotate the end effector by a certain angle, and then the manipulator is directed to pull away from the tree and detach the target fruit. Finally, the manipulator retracts to a dropping spot and releases the fruit-which is caught by the fruit catching module”).
Another closest prior art, Gong et al. (CN115338843 A, attached English translate of the foreign document CN115338843 A is used for claim mapping) teaches, in para. [n0003], “identify and locate the distribution of the fruit in advance”.
Nevertheless, the teaching of Lu and Gong et al. (CN115338843 A) fails to suggest, disclose or teach individually or in combination to render obvious limitations of “determining partial fruit positioning distribution information corresponding to each robotic arm according to the global fruit positioning distribution information, to control the robotic arms to perform collaborative operation”, and in combination with all other limitation of claim 1.
Claims 2-7 and 9-20 depends either directly or indirectly upon claim 1. Therefore, claims 2-9 would be allowable by virtue of its dependency if claims are rewritten to overcome the rejection(s) under 35 U.S.C. 112(b), 35 U.S.C. 112 (a), 35 U.S.C. 101, and claims objections for informalities, set forth in this Office action.
Claim 8. Lu et al. (IUS 2025/0081892 A1) (hereinafter Lu) teaches a fruit positioning apparatus (See Fig. 1 and/or Fig. 9), comprising:
an output module, configured to obtain fruit tree images of respective sub-areas in an operation area that are collected by respective first image collection modules (See Abstract, Para. [0018], [0022], [0029], discloses “The controller/processor processes the extracted laser line image data and determines the xyz position of the centroid of the target fruit, so that the controller/processor directs a manipulator arm to pick the fruit.”), and
input the fruit tree images into a predefined target detection model to obtain two-dimensional bounding box information and a mask area of each fruit in each fruit tree image output by the predefined target detection model (See Para. [0007], [0043], discloses “The acquired RGB-D image data is first processed using a specially developed deep learning algorithm to identify all fruits 26 in the workspace, using “bounding boxes”, as described in the fruit detection flow chart FIG. 5 and in FIG. 7. The rough localization information for all detected fruits 26 in the robot's working space is subsequently obtained by fusing the bounding boxes with the point cloud data (depth image) provided by the RGB-D camera 12.”);
a positioning module, configured to generate a three-dimensional point cloud of each fruit in each fruit tree image by using the mask area of each fruit in each fruit tree image and corresponding image depth information, and determine a first positioning coordinate point of each fruit in each fruit tree image based on the three-dimensional point cloud (See Para. [0043], “he rough localization information for all detected fruits 26 in the robot's working space is subsequently obtained by fusing the bounding boxes with the point cloud data (depth image) provided by the RGB-D camera 12.”, and Para. [0049], “The controller/processor uses the images and a laser triangulation technique to localize the fruit and to determine the xyz position of the centroid of the target fruit”), and
Lu fails to teach, where a positioning module, configured to determine the two-dimensional bounding box information of each fruit in each fruit tree image; and
a processing module, configured to determine global fruit positioning distribution information of the operation area based on a result obtained by transforming the first positioning coordinate point of each fruit in each fruit tree image to base coordinate system.
Another closest prior art, Yang et al. (CN114260895, attached English translate document is used for claim mapping) (hereinafter Yang) teaches, determine the two-dimensional bounding box information of each fruit in each fruit tree image (See [n0064], “calculating the two-dimensional center of a ripe tomato”, and see [n0065], “Assuming that the arc-shaped boundary of the visible part of the tomato is an arc, the width and height of the visible arc-shaped boundary of the tomato can be calculated using relevant formulas”); and determining a first positioning coordinate point of each fruit based on the two-dimensional bounding box information of each fruit (See [n0060], discloses “The visible arc boundary of the tomato 2D RGB image after image segmentation is the common boundary between the ripe tomato and the background, with intersection points P1 and P2. The visible arc height of the tomato 2D RGB image can be obtained from geometric relationships, and where x<sub>1</sub> is the x-coordinate of intersection point P1, y<sub>1</sub> is the y-coordinate of intersection point P1, x<sub>2< /sub> is the x-coordinate of intersection point P2”, and [n0065], discloses “From the input RGB color image, the visible part of the tomato is segmented based on color. After segmenting the tomato region and the obstacle region, the boundary is detected using an edge detection algorithm”, same as claimed); and
Nevertheless, the cited prior arts as discussed above fails to suggest, disclose or teach individually or in combination to render obvious limitations of “determine global fruit positioning distribution information of the operation area based on a result obtained by transforming the first positioning coordinate point of each fruit in each fruit tree image to base coordinate system”, and in combination with other limitations of claim 8.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to B M M HANNAN whose telephone number is (571)270-0237. The examiner can normally be reached MONDAY-FRIDAY at 8:30AM-5:30PM.
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, Adam Mott can be reached at 5712705376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/B M M HANNAN/Primary Examiner, Art Unit 3657
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