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 in response to Application No. 17/894,027, filed on 30-DEC-2024. Claims 1-23 are currently pending and have been examined. Claims 1-23 have been rejected as follows.
Claim Rejections - 35 USC § 101
Claims 1-10 and 13-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Claims 1-10 are directed to a method filtering and sorting a plurality of pick candidates in a robotic pick and place system (i.e., a process). Claims 13-22 are directed to a non-transitory computer-readable medium for filtering and sorting a plurality of pick candidates in a robotic pick and place system (i.e., a manufacture). Therefore, claims 1-10 and 13-22 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes. Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
A method for filtering and sorting a plurality of pick candidates in a robotic pick and place system comprising: receiving, from object tracking logic, tracking information for the plurality of pick candidates
applying one or more filtering rules to remove a subset of the plurality of pick candidates from consideration, the removed subset comprising pick candidates deemed by filtering logic to be unsuitable for picking
providing a remaining subset of the plurality of pick candidates to sorting logic
sorting the remaining subset of the plurality of pick candidates based on one or more sorting rules
selecting a pick candidate ranked highest by the sorting rules
and transmitting the selected pick candidate to a robotic arm of the robotic pick and place station
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process”, because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “applying …”, “providing …”, “sorting …”, and “selecting …” in the context of this claim encompasses a person assessing the pick candidates, deciding which objects are unpickable, and mentally sorting the remaining objects, and choosing the highest priority item. Accordingly, the claim recites at least 4 abstract ideas.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract idea into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”. In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A method for filtering and sorting a plurality of pick candidates in a robotic pick and place system comprising: receiving, from object tracking logic, tracking information for the plurality of pick candidates
applying one or more filtering rules to remove a subset of the plurality of pick candidates from consideration, the removed subset comprising pick candidates deemed by filtering logic to be unsuitable for picking
providing a remaining subset of the plurality of pick candidates to sorting logic
sorting the remaining subset of the plurality of pick candidates based on one or more sorting rules
selecting a pick candidate ranked highest by the sorting rules
and transmitting the selected pick candidate to a robotic arm of the robotic pick and place station
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations of “receiving …” and “transmitting …”, the examiner submits that these limitations are insignificant extra-solution activities as they are broad enough to include the pre-solution activity gathering data and post-solution activity of displaying data. In particular, the receiving and transmitting steps are recited at a high level of generality (i.e. as a general receiving tracking information and transmitting the candidates respectively), and amounts to mere data gathering and displaying which is a form of insignificant extra-solution activity. Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above, the additional limitations of “receiving…” and “transmitting…”, the examiner submits that these limitations are insignificant extra-solution activities. Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well- understood, routine, conventional activity in the field. The additional limitations “receiving…” and “transmitting…”, are well-understood, routine, and conventional activities as is merely the collection and display of data. 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), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. The Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data is a well understood, routine, and conventional function. Hence, the claim is not patent eligible.
Dependent claim(s) 2-10 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application as none of the dependent claims narrow the scope to not encompass performance of the limitations in the human mind. Therefore, dependent claims 2-10 are not patent eligible under the same rationale as provided for in the rejection of claim 1. Similarly, claim 13 is rejected under the same rationale provided for the rejection of claim 1, and dependent claims 14-22 are not patent eligible.
Therefore, claim(s) 1-10, 13-22 are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1, 3, 4, 6, 7-10, 12, 13, 15, 16, 18-22 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kumar et al. (WO 2024/138070 A1)
Regarding claim 1, Kumar et al. teaches: A method for filtering and sorting a plurality of pick candidates in a robotic pick and place system comprising: receiving, from object tracking logic, tracking information for the plurality of pick candidates (Paragraph [28], "(1) input from a perception system 142, e.g., a computer vision system, which estimates state of the workspace, including items present in the workspace and agents working therein, e.g., based on data generated by 3D cameras or other sensors present in the workspace"); applying one or more filtering rules to remove a subset of the plurality of pick candidates from consideration (Figure 1; element 108, 110), the removed subset comprising pick candidates deemed by filtering logic to be unsuitable for picking (Paragraph [28], "(2) robot models 144, representing the elements comprising and kinematics and/or other capabilities and/or limitations of each robot 102, 104 and/or other robotically-controlled agents in the workspace"); providing a remaining subset of the plurality of pick candidates to sorting logic (Paragraph [21], "In the example shown, reach circles 108 and 110 indicate the respective reachable areas of robots 102 and 104"); sorting the remaining subset of the plurality of pick candidates based on one or more sorting rules (Paragraph [33], "Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor), is it overlapping or under another box, etc."); selecting a pick candidate ranked highest by the sorting rules (Paragraph [33], "In some embodiments, the ordered list is a list determined by the perception system as the most preferable boxes to pick first...Referring further to Figure 1, an example of an ordered list received at 202 is { 1, 2, 3, 4, 5, 6}, indicating those six boxes are pickable by both robots 102, 104 in the sequential order of preference as determined by the perception system"); and transmitting the selected pick candidate to a robotic arm of the robotic pick and place station (Figure 2; element 212)
Regarding claim 3, Kumar et al. teaches: The method of claim 1, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates based on at least one of an object motion (Figure 1; element 1-8, 108, 110) an object type (Paragraph [34], "For example, in the case of packing a container or stacking on a pallet, a pair may be selected (e.g., based on size, weight, dimensions, rigidity, or other attributes)"), or an object occlusion (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
Regarding claim 4, Kumar et al. teaches: The method of claim 1, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates based on an object collision with adjacent items (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
Regarding claim 6, Kumar et al. teaches: The method of claim 1, wherein the one or more sorting rules comprise at least one rule for sorting pick candidates based on the pick candidates' pose or orientation, distance downstream along a conveyor, position across the conveyor, (Paragraph [33], "Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor), is it overlapping or under another box, etc.") or height above the conveyor (Interpreting this sorting limitation as the alternative with respect to "at least one…or"); wherein: a pick candidate having a more favorable pose or orientation for establishing an effective grip is sorted higher than a pick candidate having a less favorable pose or orientation (Interpreting this limitation as the alternative with respect to "wherein;… or") a pick candidate located further downstream along the conveyor is sorted higher than a pick candidate that is located further upstream along the conveyor (Figure 1; element 1, 114; Paragraph [33], "In some embodiments, the ordered list is a list determined by the perception system as the most preferable boxes to pick first. Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor)"); a pick candidate located closer to the robotic arm based on the pick candidate's position across the conveyor is sorted higher than a pick candidate that is located further away from the robotic arm; or a pick candidate located higher above the conveyor is sorted higher than a pick candidate located lower towards the conveyor (Interpreting this limitation as the alternative with respect to "wherein;… or")
Regarding claim 7, Kumar et al. teaches: The method of claim 1, wherein the one or more sorting rules comprise at least one rule for sorting pick candidates based on a degree of collision with adjacent objects (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping") or occlusion by other objects (Paragraph [33], "Examples of the criteria used include, without limitation... is it ... under another box, etc")
Regarding claim 8, Kumar et al. teaches: The method of claim 7, wherein the sorting rules apply the at least one rule if the filtering rules filter out more than a predetermined number or percentage of objects in the field of view (Figure 1; Interpreting this limitation as the alternative with respect to "or", considering only a percentage of objects in the field of view. It is noted that the article used is "if" and not "only if")
Regarding claim 9, Kumar et al. teaches: The method of claim 1, wherein the robotic pick and place system comprises a plurality of different robotic arms (element 102, 104), and different filtering rules or sorting rules are applied for each of the different robotic arms (Figure 1; element 108, 110)
Regarding claim 10, Kumar et al. teaches: The method of claim 9, wherein the different rules are defined based on a load balancing priority for each respective robotic arm (Paragraph [28], "(2) robot models 144, representing the elements comprising and kinematics and/or other capabilities and/or limitations of each robot 102, 104")
Regarding claim 12, Kumar et al. teaches: A system comprising: a robotic arm (element 102, 104); a conveyor for conveying objects to the robotic arm (element 106); a sensor (Paragraph [28], "based on data generated by 3D cameras or other sensors present in the workspace"); and a processor configured to perform the method of claim 1 (Paragraph [15])
Regarding claim 13, Kumar et al. teaches: A non-transitory computer-readable medium storing instructions that, when executed by one or more processors associated with a robotic pick and place system, the instructions describing a method (Paragraph [15]) for filtering and sorting a plurality of pick candidates in a robotic pick and place system comprising: receiving, from object tracking logic, tracking information for the plurality of pick candidates (Paragraph [28], "(1) input from a perception system 142, e.g., a computer vision system, which estimates state of the workspace, including items present in the workspace and agents working therein, e.g., based on data generated by 3D cameras or other sensors present in the workspace"); applying one or more filtering rules to remove a subset of the plurality of pick candidates from consideration (Figure 1; element 108, 110), the removed subset comprising pick candidates deemed by filtering logic to be unsuitable for picking (Paragraph [28], "(2) robot models 144, representing the elements comprising and kinematics and/or other capabilities and/or limitations of each robot 102, 104 and/or other robotically-controlled agents in the workspace"); providing a remaining subset of the plurality of pick candidates to sorting logic (Paragraph [21], "In the example shown, reach circles 108 and 110 indicate the respective reachable areas of robots 102 and 104"); sorting the remaining subset of the plurality of pick candidates based on one or more sorting rules (Paragraph [33], "Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor), is it overlapping or under another box, etc."); selecting a pick candidate ranked highest by the sorting rules (Paragraph [33], "In some embodiments, the ordered list is a list determined by the perception system as the most preferable boxes to pick first...Referring further to Figure 1, an example of an ordered list received at 202 is { 1, 2, 3, 4, 5, 6}, indicating those six boxes are pickable by both robots 102, 104 in the sequential order of preference as determined by the perception system"); and transmitting the selected pick candidate to a robotic arm of the robotic pick and place station (Figure 2; element 212)
Regarding claim 15, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates based on at least one of an object motion (Figure 1; element 1-8, 108, 110) an object type (Paragraph [34], "For example, in the case of packing a container or stacking on a pallet, a pair may be selected (e.g., based on size, weight, dimensions, rigidity, or other attributes)"), or an object occlusion (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
Regarding claim 16, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates based on an object collision with adjacent items (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
Regarding claim 18, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the one or more sorting rules comprise at least one rule for sorting pick candidates based on the pick candidates' pose or orientation, distance downstream along a conveyor, position across the conveyor, (Paragraph [33], "Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor), is it overlapping or under another box, etc.") or height above the conveyor (Interpreting this sorting limitation as the alternative with respect to "at least one…or"); wherein: a pick candidate having a more favorable pose or orientation for establishing an effective grip is sorted higher than a pick candidate having a less favorable pose or orientation (Interpreting this limitation as the alternative with respect to "wherein;… or") a pick candidate located further downstream along the conveyor is sorted higher than a pick candidate that is located further upstream along the conveyor (Figure 1; element 1, 114; Paragraph [33], "In some embodiments, the ordered list is a list determined by the perception system as the most preferable boxes to pick first. Examples of the criteria used include, without limitation, the proximity to the place location (it would be faster to pick and place and help advance the conveyor)"); a pick candidate located closer to the robotic arm based on the pick candidate's position across the conveyor is sorted higher than a pick candidate that is located further away from the robotic arm; or a pick candidate located higher above the conveyor is sorted higher than a pick candidate located lower towards the conveyor (Interpreting this limitation as the alternative with respect to "wherein;… or")
Regarding claim 19, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the one or more sorting rules comprise at least one rule for sorting pick candidates based on a degree of collision with adjacent objects (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping") or occlusion by other objects (Paragraph [33], "Examples of the criteria used include, without limitation... is it ... under another box, etc")
Regarding claim 20, Kumar et al. teaches: The non-transitory computer-readable medium of claim 19, wherein the sorting rules apply the at least one rule if the filtering rules filter out more than a predetermined number or percentage of objects in the field of view (Figure 1; Interpreting this limitation as the alternative with respect to "or", considering only a percentage of objects in the field of view. It is noted that the article used is "if" and not "only if")
Regarding claim 21, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the robotic pick and place system comprises a plurality of different robotic arms (element 102, 104), and different filtering rules or sorting rules are applied for each of the different robotic arms (Figure 1; element 108, 110)
Regarding claim 22, Kumar et al. teaches: The non-transitory computer-readable medium of claim 21, wherein the different rules are defined based on a load balancing priority for each respective robotic arm (Paragraph [28], "(2) robot models 144, representing the elements comprising and kinematics and/or other capabilities and/or limitations of each robot 102, 104")
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (WO 2024/138070 A1) in view Sun et al. (US 2025/0010484 A1).
Regarding claim 2, Kumar et al. teaches: the filtering and sorting are performed using a rules-based algorithm (Paragraph [33], "criteria")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
wherein the object tracking logic comprises a machine learning construct
However, Sun et al. teaches: The method of claim 1, wherein the object tracking logic comprises a machine learning construct (Paragraph [134], " In this case, the robot uses a machine learning or geometric model to predict the height of the object")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot conveyor motion planning for picking items of Kumar et al., to include machine learning to predict the height of the object, as taught by Sun et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: multiple robot conveyor motion planning that uses machine learning in predicting height position for picking items.
Regarding claim 14, Kumar et al. teaches: the filtering and sorting are performed using a rules-based algorithm (Paragraph [33], "criteria")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
wherein the object tracking logic comprises a machine learning construct
However, Sun et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the object tracking logic comprises a machine learning construct (Paragraph [134], " In this case, the robot uses a machine learning or geometric model to predict the height of the object")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot conveyor motion planning for picking items of Kumar et al., to include machine learning to predict the height of the object, as taught by Sun et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: multiple robot conveyor motion planning that uses machine learning in predicting height position for picking items.
Claim 5 and 17 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (WO 2024/138070 A1) in view Sun et al. (US 2025/0010484 A1) in further view of Xu et al. (US 20230339118 A1).
Regarding claim 5, Kumar et al. teaches: The method of claim 1, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates when the pick candidate is within a threshold proximity to an adjacent object (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
the threshold proximity being defined based on a size of a gripper of the robotic arm
However, Sun et al. teaches: the threshold proximity being defined based on a size of a gripper of the robotic arm ([114], "In the example shown in FIG. 7C, at 742 a condition in which no item can currently be grasped is detected. For example, the system may have attempted to determine grasp strategies for items in the pile, but determined that due to flow speed, clutter, orientation, overlap, etc., there is no item for which a grasp strategy having a probability of success greater than a prescribed minimum threshold is currently available"; [70], “For example, the system determines which robotic arms can reach the item and selects one with the most appropriate end effector and/or other attributes to successfully grasp the item.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot picking items from a conveyor and assigning items based on overlap with another object of Kumar et al., to include determining the grasp success probability based on the overlap of items and the end-effector, as taught by Sun et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector.
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
as determined by a three-dimensional model of the gripper
However, Xu et al. teaches: as determined by a three-dimensional model of the gripper ([52], "The refined pose of the end-effector can also be determined by template matching between the 3D point cloud of the end-effector and its geometric model.")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector of Kumar et al. and Sun et al, to include using a geometric model of the end-effector of Xu et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector’s grasp success considering its geometric model.
Regarding claim 17, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, wherein the one or more filtering rules comprise at least one rule for filtering out pick candidates when the pick candidate is within a threshold proximity to an adjacent object (Paragraph [33], "Examples of the criteria used include, without limitation... is it overlapping or under another box, etc")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
the threshold proximity being defined based on a size of a gripper of the robotic arm
However, Sun et al. teaches: the threshold proximity being defined based on a size of a gripper of the robotic arm ([114], "In the example shown in FIG. 7C, at 742 a condition in which no item can currently be grasped is detected. For example, the system may have attempted to determine grasp strategies for items in the pile, but determined that due to flow speed, clutter, orientation, overlap, etc., there is no item for which a grasp strategy having a probability of success greater than a prescribed minimum threshold is currently available"; [70], “For example, the system determines which robotic arms can reach the item and selects one with the most appropriate end effector and/or other attributes to successfully grasp the item.”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot picking items from a conveyor and assigning items based on overlap with another object of Kumar et al., to include determining the grasp success probability based on the overlap of items and the end-effector, as taught by Sun et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector.
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
as determined by a three-dimensional model of the gripper
However, Xu et al. teaches: as determined by a three-dimensional model of the gripper ([52], "The refined pose of the end-effector can also be determined by template matching between the 3D point cloud of the end-effector and its geometric model.")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector of Kumar et al. and Sun et al, to include using a geometric model of the end-effector of Xu et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including: the multiple robot picking items from a conveyor and assigning items based on overlap with another object and the gripper end-effector’s grasp success considering its geometric model.
Claim 11 and 23 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar et al. (WO 2024/138070 A1) in view Kulkarni et al. (US 20230321825 A1).
Regarding claim 11, Kumar et al. teaches: The method of claim 1, further comprising: detecting when a pick candidate reaches an end of a conveyance for the robotic pick and place system (Paragraph [33], "the proximity to the place location")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
halting the conveyance until the detected pick candidate is picked
However, Kulkarni et al. teaches: and halting the conveyance until the detected pick candidate is picked (Paragraph [87], "the robotic system controls the conveyor to slow (e.g., to delay the arrival of the destination location) or to stop the conveyor to enable the robot(s) to push/move the item to the destination location")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robots picking items from a conveyor of Kumar et al., to include stopping the conveyor to enable the robot to perform movement of the item, as taught by Kulkarni et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including multiple robots picking items from a conveyor and stopping the conveyor to enable the robot to perform movement of the item.
Regarding claim 23, Kumar et al. teaches: The non-transitory computer-readable medium of claim 13, further comprising: detecting when a pick candidate reaches an end of a conveyance for the robotic pick and place system (Paragraph [33], "the proximity to the place location")
While Kumar et al. teaches the limitations as stated above, it does not expressly teach:
halting the conveyance until the detected pick candidate is picked
However, Kulkarni et al. teaches: and halting the conveyance until the detected pick candidate is picked (Paragraph [87], "the robotic system controls the conveyor to slow (e.g., to delay the arrival of the destination location) or to stop the conveyor to enable the robot(s) to push/move the item to the destination location")
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify the multiple robots picking items from a conveyor of Kumar et al., to include stopping the conveyor to enable the robot to perform movement of the item, as taught by Kulkarni et al. Such modification would have been obvious because such application would have been well within the level of skill of a person having ordinary skill in the art and would have yielded predictable results. The predictable results including multiple robots picking items from a conveyor and stopping the conveyor to enable the robot to perform movement of the item.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALYSE TRAMANH TRAN whose telephone number is (703)756-5879. The examiner can normally be reached M-F 8:30am-5pm ET.
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/A.T.T./Examiner, Art Unit 3656 /KHOI H TRAN/Supervisory Patent Examiner, Art Unit 3656