DETAILED ACTION
Notice of AIA Status
The present application is being examined under the AIA the first inventor to file provisions.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/22/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Objections
Claim 3, 7, 9, and 20 are objected to because of the following informalities:
In claim 3, Line 4 the term “if a region exists in which” should be changed to “when a region exists in which” in order for the subject matter to be positively recited. Please see MPEP 2111. 04. Appropriate correction is required.
In claim 7, Line 4 the term “if the plurality” should be changed to “when the plurality” in order for the subject matter to be positively recited. Please see MPEP 2111. 04. Appropriate correction is required.
In claim 9, Line 4 the term “if the plurality” should be changed to “when the plurality” in order for the subject matter to be positively recited. Please see MPEP 2111. 04. Appropriate correction is required.
In claim 20, Line 2 the term “a support supporting the arm” should be changed to “ the support supporting the arm” for typographical/grammar issues to avoid clarity issues to prevent a rejection under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph.
Claims 3, 7, and 9 incudes the word “if” when reciting a conditional statement. In view of the broadest reasonable interpretation of the claims, MPEP 2111, these limitations may be interpreted in the sense that the limitations occur when the conditional statement occurs, but also introduces the possibility that the conditional statement may not occur. If the condition for performing a conditional statement is not satisfied, the functionality recited by the statement need not be carried out in order for the claimed functionality to be performed. Since the claim fails to recite any specific limitations regarding the possibility that the conditional statement may not occur, the broadest reasonable interpretation of the claim allows for the possibility wherein no functionality is achieved when the conditional statement is not achieved.
Double Patenting
The non-statutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A non-statutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on non-statutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20, are rejected on the ground of non-statutory double patenting as being unpatentable over claims 1-19 of co-pending US Patent Application No.: 18/956,518 in view of Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning).
Although the claims 1-20 of this Application No. 18/956,577 and claims at issue of co-pending US Patent Application No.: 18/956,518 are not identical, they are not patentably distinct from each other because the instant application and the conflicting co-pending US Patent Application No.: 18/956,518 are claiming common subject matter, as follows:
This Application No. 18/956,577
co-pending US Patent App. No.: 18/956,518
Claim 1: A method for using a computer or computers to generate cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off, the method comprising:
grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes, the sensor data being acquired by a sensor or sensors;
based on the sensor data, determining one or more canes having been grouped into one of the plurality of groups each as a cane to be removed or a cane to be retained;
obtains a decoded prediction residual by performing inverse transform on the decoded transform coefficient;
based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups, determining the plurality of canes each as a cane to be removed or a cane to be retained
and generating the cut-point data for each cane determined as a cane to be removed.
Claim 17: A system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off;
the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree;
and a data processor configured or programmed to generate the cut-point data for a cane of the fruit tree based on the sensor data;
wherein the data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on sensor data;
based on the sensor data, determine one or more canes to be retained from among one or more canes having been grouped into one of the plurality of groups;
based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups, determine one or more other canes to be retained from among the plurality of canes;
and generate the cut-point data for, among the plurality of canes, each cane other than the one or more canes to be retained and the one or more other canes to be retained.
Claim 1: A method using a computer or computers to generate cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off, the method comprising:
grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes acquired by a sensor or sensors;
based on the sensor data, determining one or more canes having been grouped into a same group among the plurality of groups each as a cane to be removed or a cane to be retained;
and generating the cut-point data for each cane determined to be removed.
Claim 16: A system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off:
the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree;
and at least one data processor configured or programmed to generate the cut-point data for a cane of the fruit tree based on the sensor data;
wherein the at least one data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on the sensor data;
based on the sensor data, determine one or more canes having been grouped into a same group among the plurality of groups each as a cane to be removed or a cane to be retained;
and generate the cut-point data for each cane determined as a cane to be removed.
Although, U.S. co-pending US Patent Application No.: 18/956,518, claim 1 as stated in the table above with respect to claim 1, fails to clearly disclose based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups, determining the plurality of canes each as a cane to be removed or a cane to be retained.
However, Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning), explicitly teaches based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups (Fig. 6, Section 2.2.3, Paragraph [0002]- Silwal discloses detecting buds is a critical step in the pruning process of grape vines. Pruning rules such as cane and spur pruning which are popular in commercial settings involve retaining a certain number of buds per cane.),
determining the plurality of canes each as a cane to be removed or a cane to be retained (Fig. 8, Section 4.2.6, Paragraph [0001]- Silwal discloses for a proof-of-concept robotic pruning of vines, we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of the co-pending US Patent Application No.: 18/956,518, claim 1 of having a method using a computer or computers to generate cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off, the method comprising: grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes acquired by a sensor or sensors; based on the sensor data, determining one or more canes having been grouped into a same group among the plurality of groups each as a cane to be removed or a cane to be retained; and generating the cut-point data for each cane determined as a cane to be removed with the teachings of Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning) of having based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups, determining the plurality of canes each as a cane to be removed or a cane to be retained.
Wherein having co-pending US Patent Application No.: 18/956,518 claim 1 having based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups, determining the plurality of canes each as a cane to be removed or a cane to be retained.
The motivation behind the modification would have been to improve pruning efficiency of the robotic system.
Co-pending US Patent Application No.: 18/956,518, claim 16 as stated in the table above with respect to claim 17, fails to clearly disclose based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups, determine one or more other canes to be retained from among the plurality of canes.
Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning), explicitly teaches based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups, (Fig. 6, Section 2.2.3, Paragraph [0002]- Silwal discloses detecting buds is a critical step in the pruning process of grape vines. Pruning rules such as cane and spur pruning which are popular in commercial settings involve retaining a certain number of buds per cane.),
determine one or more other canes to be retained from among the plurality of canes (Fig. 8, Section 4.2.6, Paragraph [0001]- Silwal discloses for a proof-of-concept robotic pruning of vines, we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of the co-pending US Patent Application No.: 18/956,518, claim 16 of having a system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off, the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree; and at least one data processor configured or programmed to generate the cut-point data for a cane of the fruit tree based on the sensor data; wherein the at least one data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on the sensor data; based on the sensor data, determine one or more canes having been grouped into a same group among the plurality of groups each as a cane to be removed or a cane to be retained; and generate the cut-point data for each cane determined as a cane to be removed with the teachings of Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning) of having based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups, determine one or more other canes to be retained from among the plurality of canes.
Wherein having co-pending US Patent Application No.: 18/956,518 claim 16 having based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups, determine one or more other canes to be retained from among the plurality of canes.
The motivation behind the modification would have been to improve pruning efficiency of the robotic system.
The further limitations of the dependent claims are similar as indicated below:
This Application No. 18/956,577
Co-pending US Patent App. No.: 18/956,518
Claim 4: wherein the grouping includes: based on the sensor data, grouping the plurality of canes into the plurality of groups by relying on base positions of the plurality of canes.
Claim 13: wherein the determining the one or more canes each as a cane to be removed or a cane to be retained includes: based on the sensor data, for each of the one or more canes, acquiring a measurement value(s) concerning one or more attributes; and based on the measurement value(s), determining the one or more canes each as a cane to be removed or a cane to be retained.
Claim 14: further comprising: inputting the generated cut-point data to a controller configured or programmed to control a three-dimensional position of a cutter that cuts a cane of the fruit tree.
Claim 15: further comprising: acquiring information on a number of buds to be retained on each cane having been determined as a cane to be retained; and based on the number of buds to be retained, generating the cut-point data for each cane to be retained.
Claim 16: wherein the generating the cut-point data for each cane having been determined as a cane to be retained includes: generating the cut-point data so that each cane having been determined as a cane to be retained includes one or more buds after being cut.
Claim 18: further comprising: a cutter to cut a cane of the fruit tree and a controller configured or programmed to control a three-dimensional position of the cutter; wherein the data processor is configured or programmed to input the generated cut-point data to the controller; and the controller is configured or programmed to control the three-dimensional position of the cutter based on the cut-point data.
Claim 19: An agricultural machine, comprising the system of claim 18.
Claim 20: further comprising: an arm supporting the cutter, a support supporting the arm, and a driver to move the support; wherein the controller is configured or programmed to control the three-dimensional position of the cutter by controlling an operation of the arm.
Claim 5: wherein the grouping includes: based on the sensor data, grouping the plurality of canes into the plurality of groups by relying on base positions of the plurality of canes.
Claim 2: wherein the determining the one or more canes each as a cane to be removed or a cane to be retained includes: based on the sensor data, determining a measurement value(s) concerning one or more attributes of each of the one or more canes; and determining the one or more canes each as a cane to be removed or a cane to be retained based on the measurement value(s).
Claim 4: further comprising: inputting the generated cut-point data to a controller configured or programmed to control a three-dimensional position of a cutter to cut a cane of the fruit tree.
Claim 10: further comprising: acquiring information on a number of buds to be retained on each cane to be retained; and based on the number of buds to be retained, generating the cut-point data for each cane having been determined as a cane to be retained.
Claim 12: wherein the generating the cut-point data for each cane having been determined as a cane to be retained includes: generating the cut-point data so that each cane having been determined as a cane to be retained includes one or more buds after being cut.
Claim 17: further comprising: a cutter to cut a cane of the fruit tree and a controller configured or programmed to control a three-dimensional position of the cutter; wherein the at least one data processor is configured or programmed to input the generated cut-point data to the controller; and the controller is configured or programmed to control the three-dimensional position of the cutter based on the cut-point data.
Claim 18: An agricultural machine comprising the system of claim 18.
Claim 19: further comprising: an arm supporting the cutter, a support supporting the arm, and a driver to move the support; wherein the controller is configured or programmed to control the three-dimensional position of the cutter by controlling an operation of the arm.
Claims 4, 13-16, and 18-20 contain the same limitations as Co-pending US Patent App. No.: 18/956,518 claims 5, 2, 4, 10, 12, 17-19 respectively. Therefore, given that claims 4-16 depend from claim 1 and 18-20 on claim 17. Claims 2-16 and 18-20, are rejected for the same reasons set forth in the rejection of the independent claim above.
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.
Claims 14, 18, and 20 recites limitations that use words like “means” (or “step”) or similar terms with functional language and do invoke 35 U.S.C. 112(f):
Claim 14; recites the limitation, “a controller configured or programmed to control.” [Line 2-3].
Claim 14; recites the limitation, “a cutter that cuts a cane” [Line 4].
Claim 18; recites the limitation, “a controller configured or programmed to control” [Line 2].
Claim 18; recites the limitation, “a cutter to cut a cane” [Line 2].
Claim 18; recites the limitation, “the controller is configured or programmed to control” [Line 7].
Claim 20; recites the limitation, “a support supporting the arm” [Line 2].
Claim 20; recites the limitation, “the controller is configured or programmed to control” [Line 4].
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.
After a careful analysis, as disclosed above, and a careful review of the specification the following limitations in claims 14, 18, and 20:
“a cutter” (Fig. 1, #24. Paragraph [0163]- As in the example shown in FIG. 4B, the procedure of generating cut-point data of canes of a fruit tree may further include step S400. At step S400, the cut-point data generated in step S300 is input to a controller configured or programmed to control the three-dimensional position of a cutter (the cutting tool 24 in the example of FIG. 1). (wherein cutter has structure associated with it of any cutting tool used to cut cane).)).
“a controller” (Fig. 4F, #600. Paragraph [0170]- The cutter controller 600 may be a computer or computers to control the three-dimensional position of the cutter 620 based on the cut-point data generated by the data processor 530. It is realized by a computer such as an electronic control unit (ECU) or electronic control units (ECUs), for example. In the examples of FIG. 1 and FIG. 2, the cutting tool 24 is supported on the robotic arm 22. In the case where the cutter 620 is supported on an arm as in the examples of FIG. 1 and FIG. 2, the cutter controller 600 further controls the operation of the arm supporting the cutter 620 (wherein the controller has structure associated with it of a computer.).).
“a support” (Fig. 1, #32. In Paragraph [0142]- The base frame 10 can be mounted on a base 32, and base electronics 34 can also be mounted to the base 32. A plurality of wheels 36 can be mounted to the base 32. The plurality of wheels 36 can be controlled by the base electronics 34, and the base electronics 34 can include a power supply 35 to drive an electric motor 37 or the like, as shown in FIGS. 3A and 3B, for example. As an example, the plurality of wheels 36 can be driven by an electric motor 37 with a target capacity of about 65 kW to about 75 kW and a power supply 35 for the electric motor 37 can be a battery with a capacity of about 100 kWh. Further in Paragraph [0171]- As in the example of FIG. 1, in the case where the cutting system is mounted on an agricultural machine including a vehicle, the cutting system includes the cutting tool 24, the robotic arm 22 supporting the cutting tool 24, the base (support) 32 supporting the robotic arm 22, and a driver to move the base 32. (wherein since Fig. 1, shows a support being between the wheels the support has structure associated with it of a vehicle with a base that is between 2 wheels that are mounted to the base.).).
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6 and 11-20 are rejected under 35 U.S.C 103 as being unpatentable over Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning) hereafter referenced as Silwal in view of Koselka et al. (US 20130204437 A1) hereafter referenced as Koselka.
Regarding claim 1, Silwal teaches a method for using a computer or computers to generate cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off (Fig. 9, Section 4.2.7, Paragraph [0004]- Silwal discloses to calculate the cut-point orientation, we projected cane segments as 3D vectors on all three perpendicular planes. Here a 3D vector is defined by the 3D coordinates of the Nth and (N +1)th bud section of the each cane that are projected to the XY, YZ, and ZX plane. The angles made by the projected line to the respective planes then provide the roll, pitch and yaw angles with respect to the reference frame. The mid-point of the vector was taken as the pruning location.),
based on a distribution of buds on the cane(s) determined as a cane(s) to be retained for each of the plurality of groups (Fig. 6, Section 2.2.3, Paragraph [0002]- Silwal discloses detecting buds is a critical step in the pruning process of grape vines. Pruning rules such as cane and spur pruning which are popular in commercial settings involve retaining a certain number of buds per cane.),
determining the plurality of canes each as a cane to be removed or a cane to be retained (Fig. 8, Section 4.2.6, Paragraph [0001]- Silwal discloses for a proof-of-concept robotic pruning of vines, we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
and generating the cut-point data for each cane determined to be removed (Fig. 9, Section 4.2.7, Paragraph [0004]- Silwal discloses to calculate the cut-point orientation, we projected cane segments as 3D vectors on all three perpendicular planes. Here a 3D vector is defined by the 3D coordinates of the Nth and (N +1)th bud section of the each cane that are projected to the XY, YZ, and ZX plane. The angles made by the projected line to the respective planes then provide the roll, pitch and yaw angles with respect to the reference frame. The mid-point of the vector was taken as the pruning location.).
Silwal is silent to explicitly teach the method comprising: grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes, the sensor data being acquired by a sensor or sensors based on the sensor data, determining one or more canes having been grouped into one of the plurality of groups each as a cane to be removed or a cane to be retained.
However, Koselka explicitly teaches the method comprising: grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes (Fig. 1, Paragraph [0061]- Koselka discloses hence, the pruning process involves observing the entire cordon before selecting the best eight before pruning the remaining canes.),
the sensor data being acquired by a sensor or sensors (Fig. 1, Paragraph [0043]- Koselka discloses the function of the map is to allow the robot to make intelligent decisions and perform tasks based on what the vision system or other attached sensors detect along with rules or algorithms in the robots software.);
based on the sensor data, determining one or more canes having been grouped into one of the plurality of groups each as a cane to be removed or a cane to be retained (Fig. 1, Paragraph [0061]- Koselka discloses hence, the pruning process involves observing the entire cordon before selecting the best eight before pruning the remaining canes.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Silwal of having a method for using a computer or computers to generate cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off with the teachings of Koselka the method comprising: grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes, the sensor data being acquired by a sensor or sensors based on the sensor data, determining one or more canes having been grouped into one of the plurality of groups each as a cane to be removed or a cane to be retained.
Wherein having Silwal’s system for automated pruning of fruit trees using a robot wherein the method comprising: grouping a plurality of canes of the fruit tree into a plurality of groups based on sensor data of the plurality of canes, the sensor data being acquired by a sensor or sensors; based on the sensor data, determining one or more canes having been grouped into one of the plurality of groups each as a cane to be removed or a cane to be retained.
The motivation behind the modification would have been to allow for greater efficiency, consistency, quality, safety, and reduced expense, since both Silwal and Koselka are both systems that use robots to prune fruit trees. Wherein Silwal’s system wherein improved the pruning efficiency, while Koselka’s system provides a way to improve efficiency, consistency, and quality while reducing expense. Please see Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning), Section 7, Paragraph [0001] and Koselka et al. (US 20130204437 A1) Paragraph [0005].
Regarding claim 2, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches wherein the distribution of buds includes a density of placement of the buds along a direction that is in line with a direction in which a cordon supporting the plurality of canes extends (Fig. 6, Section 2.2.3, Paragraph [0002]- Silwal discloses detecting buds is a critical step in the pruning process of grape vines. Pruning rules such as cane and spur pruning which are popular in commercial settings involve retaining a certain number of buds per cane.) (wherein buds per cane is seen as a density of buds).).
Regarding claim 3, Silwal in view of Koselka teaches the method of claim 2, Silwal further teaches wherein the determining the plurality of canes each as a cane to be removed or a cane to be retained includes: if a region exists in which the density of placement of the buds is locally low, among the plurality of canes (Fig. 14, Section 5.1 Paragraph [0001]- Silwal discloses Here, “4 buds” is used as a reference as the simplified spur pruning rule adopted in this study only required to retain 4 buds per cane (wherein 4 is seen as a low number).),
determining the cane(s) to be retained from among the one or more canes having been grouped into a group that is located near the region (Section 4.2.7 Paragraph [0003]- Silwal discloses pruning rules require the correct ordering and numbering of buds per canes, which in our case requires to properly assign each bud to its respective location in the canes.).
Regarding claim 4, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches wherein the grouping includes: based on the sensor data, grouping the plurality of canes into the plurality of groups by relying on base positions of the plurality of canes (Fig. 8, Section 4.2.5 paragraph [0001]- Silwal discloses using this local shape information, we were able to segment out the linear portions of a cane from cane-cordon or cane-cane intersection regions which have non-linear 3D distribution in the local neighborhood).
Regarding claim 5, Silwal in view of Koselka teaches the method of claim 4, Silwal further teaches wherein the plurality of groups correspond to a plurality of spurs of a cordon supporting the plurality of canes (Fig. 8, Section 4.2.5 paragraph [0001]- Silwal discloses based on the inference from the SVM, the set of extracted points were then labeled as a part of cane or intersection region between cane and cordon (wherein the intersection region between a cane and cordon is seen as a spur).);
and the grouping includes: based on the sensor data, among the plurality of canes, grouping any canes growing from a same spur among the plurality of spurs into a same group (Fig. 8, Section 4.2.5 paragraph [0001]- Silwal discloses using this local shape information, we were able to segment out the linear portions of a cane from cane-cordon or cane-cane intersection regions which have non-linear 3D distribution in the local neighborhood).
Regarding claim 6, Silwal in view of Koselka teaches the method of claim 4, Silwal further teaches wherein, the plurality of groups correspond to a plurality of regions of a cordon supporting the plurality of canes (Fig. 8, Section 4.2.5 paragraph [0001]- Silwal discloses based on the inference from the SVM, the set of extracted points were then labeled as a part of cane or intersection region between cane and cordon.),
the regions being arranged along a direction in which the cordon extends (Fig. 7, Section 4.2.4 paragraph [0001]- Silwal discloses to define cordon and trellis wire as obstacles, a RANSAC algorithm fitted two (vertical and horizontal) lines in the 3D model of the vines (Fig. 7 right) (wherein Fig. 7, shows regions arranged along the cordon).);
and the grouping includes: based on the sensor data, among the plurality of canes, grouping any canes growing from a same region among the plurality of regions into a same group (Fig. 8, Section 4.2.5 paragraph [0001]- Silwal discloses using this local shape information, we were able to segment out the linear portions of a cane from cane-cordon or cane-cane intersection regions which have non-linear 3D distribution in the local neighborhood).
Regarding claim 11, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches further comprising: acquiring information on the cultivation method of the fruit tree (Fig. 9, Section 4.2.6 Paragraph [0001]- Silwal discloses we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
wherein the determining the plurality of canes each as a cane to be removed or a cane to be retained includes: determining the plurality of canes each as a cane to be removed or a cane to be retained based on the distribution of buds and the cultivation method (Fig. 9, Section 4.2.6 Paragraph [0001]- Silwal discloses Pruning rules define a systematic way to remove older canes to keep the vigor and vine balance in control. Cane pruning and spur pruning are two of the most practiced pruning strategies in the U.S. grape industry. One major difference between these two rules is the number of buds retained after pruning.).
Regarding claim 12, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches further comprising: acquiring information on a number of buds to be retained on each cane to be retained (Fig. 9, Section 4.2.6 Paragraph [0001]- Silwal discloses we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
wherein the determining the plurality of canes each as a cane to be removed or a cane to be retained includes: acquiring information on the distribution of buds based on the number of buds to be retained and on the cane(s) to be retained (Fig. 9, Section 4.2.7 Paragraph [0003]- Silwal discloses newly discovered buds with respect to the root node were sequentially ordered, and the pruning points were identified using the pruning rule described in the previous Section.).
Regarding claim 13, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches wherein the determining the one or more canes each as a cane to be removed or a cane to be retained includes: based on the sensor data, for each of the one or more canes, acquiring a measurement value(s) concerning one or more attributes (Fig. 6, Section 4.2.3 Paragraph [0002]- Silwal discloses to count buds, we leverage on the robustness of deep learning-based 2D object detection in the color images of the vines.);
and based on the measurement value(s), determining the one or more canes each as a cane to be removed or a cane to be retained (Fig. 6, Section 4.2.7 Paragraph [0003]- Silwal discloses pruning rules require the correct ordering and numbering of buds per canes, which in our case requires to properly assign each bud to its respective location in the canes.).
Regarding claim 14, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches further comprising: inputting the generated cut-point data to a controller configured or programmed to control a three-dimensional position of a cutter that cuts a cane of the fruit tree (Fig. 10, Section 4.3.1, Paragraph [0003]- Silwal one way to define obstacles for motion planning could be to take the entire vine structure as obstacle and force planning algorithms to find solutions for all pruning locations. However, motion planning with collision detection and avoidance can be computationally expensive, especially in the unstructured and complex environment of dormant vines. The random arrangement of canes in the robot’s workspace as obstacles could result in the failure to converge to a solution or-as seen in practice- generate trajectories that result in erratic movements of the arm. To avoid such situations, collisions between the arm and the canes were allowed whereas trunk, trellis and cordon that are more structured and easier to identify were considered as obstacles. In addition to this, once a cutting action was executed, the arm always retracted backward to the initial pose (similar to the pose shown in Fig 3 right) before planning the path to the next pruning location.).
Regarding claim 15, Silwal in view of Koselka teaches the method of claim 1, Silwal further teaches further comprising: acquiring information on a number of buds to be retained on each cane having been determined as a cane to be retained (Fig. 9, Section 4.2.6 Paragraph [0001]- Silwal discloses we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
and based on the number of buds to be retained, generating the cut-point data for each cane to be retained (Fig. 9, Section 4.2.7 Paragraph [0003]- Silwal discloses on these unique paths, newly discovered buds with respect to the root node were sequentially ordered, and the pruning points were identified using the pruning rule described in the previous Section.).
Regarding claim 16, Silwal in view of Koselka teaches the method of claim 15, Silwal further teaches wherein the generating the cut-point data for each cane having been determined as a cane to be retained includes: generating the cut-point data so that each cane having been determined as a cane to be retained includes one or more buds after being cut (Fig. 9, Section 4.2.6 Paragraph [0001]- Silwal discloses we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.).
Regarding claim 17, Silwal discloses a system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off (Fig. 9, Section 4.2.7, Paragraph [0004]- Silwal discloses to calculate the cut-point orientation, we projected cane segments as 3D vectors on all three perpendicular planes. Here a 3D vector is defined by the 3D coordinates of the Nth and (N +1)th bud section of the each cane that are projected to the XY, YZ, and ZX plane. The angles made by the projected line to the respective planes then provide the roll, pitch and yaw angles with respect to the reference frame. The mid-point of the vector was taken as the pruning location.),
and a data processor configured or programmed to generate the cut-point data for a cane of the fruit tree based on the sensor data (Fig. 9, Section 4.2.7, Paragraph [0004]- Silwal discloses to calculate the cut-point orientation, we projected cane segments as 3D vectors on all three perpendicular planes. Here a 3D vector is defined by the 3D coordinates of the Nth and (N +1)th bud section of the each cane that are projected to the XY, YZ, and ZX plane. The angles made by the projected line to the respective planes then provide the roll, pitch and yaw angles with respect to the reference frame. The mid-point of the vector was taken as the pruning location.);
based on a distribution of buds on the one or more canes to be retained determined for each of the plurality of groups (Fig. 6, Section 2.2.3, Paragraph [0002]- Silwal discloses detecting buds is a critical step in the pruning process of grape vines. Pruning rules such as cane and spur pruning which are popular in commercial settings involve retaining a certain number of buds per cane.),
determine one or more other canes to be retained from among the plurality of canes (Fig. 8, Section 4.2.6, Paragraph [0001]- Silwal discloses for a proof-of-concept robotic pruning of vines, we adopted a simplified spur pruning rule to only retain 4 buds per cane. In addition to bud retention, pruning rules also necessitate qualitative parameters such as cane diameter and health of canes and buds. In this proof-of-concept design, we considered all canes for pruning and list the inclusion of qualitative parameters as future enhancements.);
and generate the cut-point data for, among the plurality of canes, each cane other than the one or more canes to be retained and the one or more other canes to be retained (Fig. 9, Section 4.2.7, Paragraph [0004]- Silwal discloses to calculate the cut-point orientation, we projected cane segments as 3D vectors on all three perpendicular planes. Here a 3D vector is defined by the 3D coordinates of the Nth and (N +1)th bud section of the each cane that are projected to the XY, YZ, and ZX plane. The angles made by the projected line to the respective planes then provide the roll, pitch and yaw angles with respect to the reference frame. The mid-point of the vector was taken as the pruning location.).
Silwal is silent to explicitly teach the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree; wherein the data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on sensor data; based on the sensor data, determine one or more canes to be retained from among one or more canes having been grouped into one of the plurality of groups.
However, Koselka explicitly teaches the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree (Fig. 1, Paragraph [0043]- Koselka discloses the function of the map is to allow the robot to make intelligent decisions and perform tasks based on what the vision system or other attached sensors detect along with rules or algorithms in the robots software.);
wherein the data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on sensor data (Fig. 1, Paragraph [0061]- Koselka discloses hence, the pruning process involves observing the entire cordon before selecting the best eight before pruning the remaining canes.);
based on the sensor data, determine one or more canes to be retained from among one or more canes having been grouped into one of the plurality of groups (Fig. 1, Paragraph [0061]- Koselka discloses hence, the pruning process involves observing the entire cordon before selecting the best eight before pruning the remaining canes.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Silwal of having discloses a system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off with the teachings of Koselka the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree; wherein the data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on sensor data; based on the sensor data, determine one or more canes to be retained from among one or more canes having been grouped into one of the plurality of groups.
Wherein having Silwal’s system for automated pruning of fruit trees using a robot wherein the system comprising: a sensor or sensors to acquire sensor data of a plurality of canes of the fruit tree; wherein the data processor is configured or programmed to: group the plurality of canes into a plurality of groups based on sensor data; based on the sensor data, determine one or more canes to be retained from among one or more canes having been grouped into one of the plurality of groups.
The motivation behind the modification would have been to allow for greater efficiency, consistency, quality, safety, and reduced expense, since both Silwal and Koselka are both systems that use robots to prune fruit trees. Wherein Silwal’s system wherein improved the pruning efficiency, while Koselka’s system provides a way to improve efficiency, consistency, and quality while reducing expense. Please see Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning), Section 7, Paragraph [0001] and Koselka et al. (US 20130204437 A1) Paragraph [0005].
Regarding claim 18, Silwal in view of Koselka teaches the system of claim 17, Silwal further teaches further comprising: a cutter to cut a cane of the fruit tree (Fig. 4, Section 4.1.2 Paragraph [0003]- Silwal discloses a popular choice among professional pruners to prune grape vines is bypass pruning shears. This variety of pruning shears have blades that completely “bypass” each other for precise cuts and clean separations of the canes (wherein the pruning shears are seen as a cutter).).
and a controller configured or programmed to control a three-dimensional position of the cutter (Fig. 12, Section 4.5.1 Paragraph [0001]- Silwal discloses the standalone integrated system with all perception, manipulation, and navigation components, and hardware are shown in Fig. 12. All electrical components including the computers, RTK-GPS, and cameras were powered by the ground robot’s battery except for the arm that was powered with the portable 1000 Watt gas generator for the AC control box. The edge field server ran on an Intel Xeon E5-2687Wv4 processor with 32GB of RAM and an NVIDIA GeForce GTX1080 GPU for deep neural networks inferencing. (wherein the Edge field server is seen as the controller).);
wherein the data processor is configured or programmed to input the generated cut-point data to the controller (Fig. 10, Section 4.3.1, Paragraph [0003]- Silwal one way to define obstacles for motion planning could be to take the entire vine structure as obstacle and force planning algorithms to find solutions for all pruning locations. However, motion planning with collision detection and avoidance can be computationally expensive, especially in the unstructured and complex environment of dormant vines. The random arrangement of canes in the robot’s workspace as obstacles could result in the failure to converge to a solution or-as seen in practice- generate trajectories that result in erratic movements of the arm. To avoid such situations, collisions between the arm and the canes were allowed whereas trunk, trellis and cordon that are more structured and easier to identify were considered as obstacles. In addition to this, once a cutting action was executed, the arm always retracted backward to the initial pose (similar to the pose shown in Fig 3 right) before planning the path to the next pruning location.);
and the controller is configured or programmed to control the three-dimensional position of the cutter based on the cut-point data (Fig. 9 Section 4.2.7 Paragraph [0004]- Silwal discloses once the pruning locations were identified, the next step in the pipeline was to compute its pose (position and orientation). A full pose was required as the cutting tool needs to approach the bud with a certain orientation to successfully make the cut.).
Regarding claim 19, Silwal in view of Koselka teaches the system of claim 18, Silwal further teaches an agricultural machine comprising the system of claim 18 (Fig. 12, Section 4.5.1 Paragraph [0001]- Silwal discloses the rugged ground robot (Warthog, Clear path Robotics Inc.) fitted with a custom aluminum extrusion frame provided a base platform for the gantry system and the field server. The standalone integrated system with all perception, manipulation, and navigation components, and hardware are shown in Fig. 12 (wherein machine shown in Fig. 12 is seen as a agricultural machine).).
Regarding claim 20, Silwal in view of Koselka teaches the agricultural machine of claim 19, Silwal further teaches further comprising: an arm supporting the cutter (Fig. 4, Section 4.1.2 Paragraph [0003]- Silwal discloses the combination of lightweight materials, simple machine, and high torque servo motor ensured a small (0.45 kg) yet powerful end-effector that fell well within the payload capacity (5 kg) of the robot arm),
wherein the controller is configured or programmed to control the three-dimensional position of the cutter by controlling an operation of the arm (Fig. 12, Section 4.5.1 Paragraph [0001]- Silwal discloses the standalone integrated system with all perception, manipulation, and navigation components, and hardware are shown in Fig. 12. All electrical components including the computers, RTK-GPS, and cameras were powered by the ground robot’s battery except for the arm that was powered with the portable 1000 Watt gas generator for the AC control box. The edge field server ran on an Intel Xeon E5-2687Wv4 processor with 32GB of RAM and an NVIDIA GeForce GTX1080 GPU for deep neural networks inferencing. (wherein the Edge field server is seen as the controller).).
Silwal fails to explicitly teach a support supporting the arm, and a driver to move the support.
However, Koselka explicitly teaches a support supporting the arm (Fig. 1, Paragraph [0091]- Koselka discloses the scout robot comprises a platform shown as "Scout Platform". In addition to being the main robot frame and the base for arms wherein each arm is referenced in FIG. 1 as "Arm", the platform houses the main power components, which may comprise but is not limited to components such as an engine, generator, hydraulic pump, drive train and steering system (wherein the Scout platform is seen as the support and is seen positioned between the drive wheels in Fig. 1. Please see annotated Fig. 1 below).),
and a driver to move the support (Fig. 1, Paragraph [0091]- Koselka discloses the scout robot comprises a platform shown as "Scout Platform". In addition to being the main robot frame and the base for arms wherein each arm is referenced in FIG. 1 as "Arm", the platform houses the main power components, which may comprise but is not limited to components such as an engine, generator, hydraulic pump, drive train and steering system (wherein the engine, generator, hydraulic pump, drive train and steering system are seen as drivers).);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to combine the teachings of Silwal of having discloses a system for generating cut-point data including information indicating a three-dimensional position of a point on a cane of a fruit tree where the cane is to be cut off with the teachings of Koselka a support supporting the arm, and a driver to move the support.
Wherein having Silwal’s system for automated pruning of fruit trees using a robot wherein a support supporting the arm, and a driver to move the support.
The motivation behind the modification would have been to allow for greater efficiency, consistency, quality, safety, and reduced expense, since both Silwal and Koselka are both systems that use robots to prune fruit trees. Wherein Silwal’s system wherein improved the pruning efficiency, while Koselka’s system provides a way to improve efficiency, consistency, and quality while reducing expense. Please see Silwal et al. (Bumblebee: A Path Towards Fully Autonomous Robotic Vine Pruning), Section 7, Paragraph [0001] and Koselka et al. (US 20130204437 A1) Paragraph [0005].
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Annotated Diagram of Koselka’s Fig. 1 illustrating how the support is located between the wheels that are used to move the robotic system.
Allowable Subject Matter
Claims 7 and 9 along with their dependent claims 8 and 10 respectively, are therefrom objected to as being dependent upon rejected base claim, claims 1, respectively but would be allowable if rewritten in independent form including all of the limitations of the base claims and any intervening claims, once the claim objections, and double patenting rejection are overcome.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 7, the prior arts fail to explicitly teach, if the plurality of groups include a first group into which no canes have been grouped, determining the cane(s) to be retained from among the one or more canes having been grouped into a group that is adjacent to the first group, as claimed in claim 7.
Regarding claim 9, the prior arts fail to explicitly teach, if the plurality of groups include a second group which include no canes to be retained, determining the cane(s) to be retained from among one or more canes having been grouped into a group that is adjacent to the second group, as claimed in claim 9.
Examiner’s remarks
Claims 1 and 17 were analyzed for rejection under 101, the 101 rejection was not given due to the claims being directed towards the inventive concept of the invention.
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered
pertinent to applicant`s disclosure.
MORCELLET et al. (FR 2994057 A1)- The robot has a movable structure (1) moving between rows of vine grapes. A collecting unit collects the image related to the vine grapes and branches. A treatment unit (3) treats the image. A controlling unit (30) is connected with the treatment unit to direct a cutting unit (4) on cutting points. The collecting unit includes a projection unit (20). A reading and recording unit (21) reads and records a series of the images to project the laser beam on the vine grapes and branches....................Please see Fig. 1. Abstract.
Yang et al. (CN 113111830 A)- A grape vine winter shear point detection algorithm, belonging to the technical field of target detection. It comprises the following steps: step one, dividing grapevine area; step two, thinning and vectorizing grape vine area; step three, grape vine connection relation reconstruction; step four, finding the grape vine branch needed to be prune; step five, detecting bud point and determining pruning point. The invention uses SLIC super-pixel method to divide grapevine area and background area in grapevine image; the single pixel point is aggregated as pixel block to greatly accelerate the speed of dividing; using the colour information characteristic and texture information characteristic as the division basis to train the BPNN classifier, improving the accuracy of the division; using the thinning algorithm, reducing the thinning time, improving the thinning precision, reducing the redundant pixel point, realizing the single pixel of the refining result; The invention reconstructs the grafted grapevine framework in branch connection relation, which effectively avoids the redundancy detection of other grape vine branches without pruning, and improves the efficiency.....................Please see Fig. 1. Abstract.
Horn et al. (US 4543775 A)- Cordon-trained grape vines are pruned by positioning circular saw blades to form a cutting path of predetermined size and shape above and on both sides of the horizontal trellis wire on which the cordons are trained and by translating the cutting path along the trellis wire while maintaining the size and shape of the cutting path substantially constant, while maintaining the sides of the cutting path centered on the cordons and maintaining the upper part of the cutting path at a desired height above the cordons......................Please see Fig. 1. Abstract.
Koselka et al. (US 20060213167 A1)- An agricultural robot system and method of harvesting, pruning, culling, weeding, measuring and managing of agricultural crops. Uses autonomous and semi-autonomous robot(s) comprising machine-vision using cameras that identify and locate the fruit on each tree, points on a vine to prune, etc., or may be utilized in measuring agricultural parameters or aid in managing agricultural resources. The cameras may be coupled with an arm or other implement to allow views from inside the plant when performing the desired agricultural function. A robot moves through a field first to "map" the plant locations, number and size of fruit and approximate positions of fruit or map the cordons and canes of grape vines. Once the map is complete, a robot or server can create an action plan that a robot may implement. An action plan may comprise operations and data specifying the agricultural function to perform.......................Please see Fig. 1. Abstract.
King et al. (US 20260231847 A1)- Systems, methods, and articles for generating actions to meet one or more target metrics for crops based on crop data received via images. The systems disclosed herein generate target metrics for at least one crop and images depicting at least one aspect of at least one crop. The systems disclosed herein further identify aspects of the at least one crop based on the images and generate an indicator regarding the growth of the at least one crop based on the identified aspects. The growth indicator and identified aspects are used to predict whether one or more target metrics will be met by the at least one crop. An action to meet the target metrics is generated based on the growth indicator, the prediction, and the identified aspects.......................Please see Fig. 1. Abstract.
Andros et al. (US 20140000232 A1)- A device for pruning plant material includes a frame, a vertical arm extending from the frame, and an angled pruning head extending from the vertical arm. The angled pruning head includes at least one cutting disk attached to a first shaft, and an anvil assembly having at least one anvil pair attached to a second shaft. The first and second shafts are substantially parallel to one another. The at least one cutting disk is aligned to be selectively positionable between the anvils of the at least one anvil pair.......................Please see Fig. 1. Abstract.
DELJKOVIC et al. (US 20230079259 A1)- A method comprising: activating a strobed or pulsed illumination source to produce illuminating light; polarising the illuminating light in a first polarisation axis; illuminating at least part of a tall plant crop with the polarised illuminating light to produce reflected illuminating light; polarising the reflected illuminating light in a second polarisation axis transverse to the first polarisation axis produce cross-polarised reflected illuminating light; capturing an image of at least part of the tall plant crop using the cross-polarised reflected illuminating light; and analysing the captured image to determine a condition of the tall plant crop. Also a vehicle mounted image capture system, a vehicle mounted spraying system and a plant health management system.......................Please see Fig. 1. Abstract.
George et al. (US 20130199089 A1)- An apparatus (20) for use in stripping irregular material (8) from a line (3, 4) during relative movement between the apparatus (20) and line (3, 4), including a material guide (50), stripping mechanism (40) and line guide (30). A first line guide element(30a), first stripping element (40a) and first material guide element (50a) collectively form a first stripping assembly and the second line guide element (30b), second stripping element (40b) and second material guide element (50b) collectively form a second stripping assembly, the line passing between said stripping assemblies during said stripping. The stripping assemblies are orientated during said stripping such that the first material guide rotation axis and the first stripping element rotation axis are on a first lateral side of the line and the second material guide rotation axis and the second stripping element rotation axis are on a second lateral side of the line........................Please see Fig. 1. Abstract.
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/LUCIUS CAMERON GREEN ALLEN/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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