Office Action 4: Notice of Allowance (2025-03-04)

CLAIMS:
Amendments to the Claims:

This listing of claims will replace all prior version, and listings, of claims in the application:

Claim 1 (Currently Amended) A robot for assembling a piece of furniture, the robot comprising:a base;
a robotic arm coupled to the base at a first end of the robotic arm;
a multi-functional robotic head coupled to the robotic arm at a second end of the robotic arm, the multi-functional robotic head comprising:
a camera positioned on a periphery of the multi-functional robotic head, the camera being configured to:
scan a barcode positioned on a part presented to the robot as the part rests on a conveyor, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture the instructions including co-ordinates of a first position of the part for attaching a first hardware component; and
capture an image of the part presented to the robot;
a first applicator mechanism configured to apply an adhesive to the part;
a first gripping mechanism configured to grip a first hardware component,
the first hardware component being manoeuvred by the robotic arm to a first position to be attached to the part;
a first attachment mechanism configured to attach the first hardware component to the part at the first position via a fastener to assemble the piece of furniture; and
a computing unit in communication with the robotic arm and the multi-functional robotic head, the computing unit configured to:
receive the instructions and the image of the part from the camera;
process the instructions to determine the first hardware component to attach to the part;
process the image to determine dimensions and an orientation of the part as the part rests on the conveyor;

based on the dimensions, the orientation and the co-ordinates of the first position, locate the first position ofthe part to provide the first hardware component; and
control the robotic arm and the multi-functional robotic head to:place the first hardware component at the first position of the part with the first gripping mechanism; and
while the first gripping mechanism holds the first hardware component at the first position of the part, attach the first hardware component to the part at the first position with the first attachment mechanism.

Claim 2 (Cancelled).

Claim 3 (Cancelled)

Claim 4 (Original) The robot of claim 1, wherein the processor is configured to determine a position on the part to apply the adhesive based on the instructions provided by the barcode.

Claim 5 (Cancelled)

Claim 6 (Original) The robot of claim 1, wherein the gripping mechanism is a pair of parallel plates.

Claim 7 (Original) The robot of claim 1, wherein the first hardware component is a hinge mounting plate.

Claim 8 (Original) The robot of claim 1, wherein the processor is further configured to direct the robotic arm to pick up the hinge mounting plates from a hardware provider.

Claim 9 (Original) The robot of claim 1, wherein the multi-functional robotic head further comprises a second gripping mechanism configured to grip a second hardware component.

Claim 10 (Previously Presented) The robot of claim 9, wherein the second hardware component is a slide and a slide spacer.

Claim 11 (Cancelled).

Claim 12 (Original) The robot of claim 1, wherein the multi-functional robotic head further comprises a second applicator mechanism configured to apply a third hardware component to the part.

CIaims 13-15 (Cancelled).
CIaim 16 (Currently Amended) A method of assembling a piece of furniture with a robot, the method comprising:scanning a barcode on a part by a camera positioned on a periphery of a multi- functional robotic head of the robot, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture,the instructions including co-ordinates of a first position of the part for attaching a first hardware component;
capturing an image of the part presented to the robot by the camera positioned on the robotic head;
processing the instructions to determine a first hardware component to attach to the part;
processing the image to determine dimensions and an orientation of the part as the part rests on a conveyor;
based on the dimensions, the orientation and the co-ordinates of the first position,locatinga first position ofthe part at which to place the first hardware component;
placing the first hardware component on the part at the co-ordinates of the first position; and
attaching the first hardware component to the part at the first position by a first attachment mechanism of the robot.
ClIaims 17-19 (Cancelled).
CIaim 20 (Previously Presented) The method of claim 16, wherein selecting the first h rdware component is a hinge mounting plate to attach to the part by the robot.
CIaim 21 (Previously Presented) The method of claim 20, wherein placing the hinge mounting plate on the part includes manoeuvring a multi-functional robotic head of the robot to a first storage location and gripping the hinge mounting plate by a first gripper of the multi- functional robotic head of the robot.
CIaim 22 (Cancelled).

Claim 23 (Previously Presented) The method of claim 21 further comprising selecting a second hardware component to attach to the part, the second hardware component including a slide and a slide spacer.

Claim 24 (Original) The method of claim 23, wherein selecting the slide and slide spacer to attach to the part by the robot includes manoeuvring a multi-functional robotic head of the robot to a second storage location and gripping the slide and a slide spacer by the second gripper of the multi-functional robotic head of the robot.

Claim 25 (Original) The method of claim 24, further comprising manoeuvring the second hardware component to a second position to be attached to the part, the second position determined by the robot based on the instructions provided to the robot.

Claim 26 (Original) The method of claim 25, further comprising attaching the second hardware component to the part by the robot.

Claim 27 (Original) The method of claim 26 further comprising, after attaching the second hardware component to the part by the robot, selecting a third hardware component to attach to the part.

Claim 28 (Original) The method of claim 27, wherein selecting the third hardware component to attach to the part by the robot includes selecting an adjustable shelf bracket to attach to the part by the robot.

Claims 29-37 (Cancelled).3036

OFFICE ACTION:
ALLOWANCE
Claims 1, 6-10, 12, 15, 20-21 and 23-28 are allowed. Claims 2-3, 5, 11, 13-15, 17-19, 22 and 29-37 were canceled. Claims 1 and 16 are the independent claim.
This application claims priority to PCT/CA2020/050163 (Canada) filed 2/7/2020, which claims priority to provisional application 62/802876, filed 2/8/2019.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The following is an examiner’s statement of reasons for allowance: The claims disclose a furniture assembly robot having a base, robotic arm and multi-functional head with a camera. The camera is configured to scan a barcode that is positioned on a part presented to the robot as it rests on a conveyer. The barcode provides instructions comprising co-ordinates of a first position of the part to be attached to the first hardware component. The image of the part presented to the robot is captured. A first applicator applies adhesive to the part while a first gripping mechanism grips the first hardware component and is maneuvered by the robotic arm to a first position to be attached to the part. An attachment mechanism attaches the first hardware component to the part at the first position using fasteners to assemble the piece of furniture. A computing unit in communication with the robotic arm and head receives instructions and the image of the part from the camera. The computing unit processes the instructions to determine the firs hardware component to be attached to the part. The image is processed to determine dimensions and orientation of the part has it rests on the conveyer. The dimensions, orientation and co-ordinates of the first position that were determined by the barcode are used to locate the first position of the part to provide the first hardware component and control the robotic arm and head to place it at the first position with the gripping mechanism. While the gripping mechanism holds the first hardware component at the first position of the part the first hardware component is attached to the part at the first position with the first attachment mechanism. Independent claim 16 is broader and omits the applicator, gripping and attachment mechanisms in addition to describing the configuration of the robot which includes the head, arm etc. The claimed features support variability in mounting locations by using barcodes that define co-ordinates of the part for attachment to the hardware component (see applicant’s specification paragraphs 3-5 and 98).
The cited reference of Chen (U.S. 4,613,942) discloses obtaining robot assembly operation instructions based on captured indica placed on a part using a camera 14 that views the indicia 12 in its field of vision (see col. 2, lines 55-65). Chen fails to teach or suggest reading a barcode that provides attachment instructions that explicitly define co-ordinates of a first position of the part for attaching a first hardware component. Instead, Chen references indicia that use shapes and color to identify components for assembly.
The cited reference of Heping (U.S. Pub 2011/0087360) discloses application of a robot for parts assembly on a workpiece moving in an assembly line and includes a camera mounted on the robot tool itself (see fig. 5, paragraphs 41 and 59).  The camera further capturing image of the presented workpiece from the assembly line and performing image processing to identify patterns of bolts/studs (see paragraph 35). Thereby teaching capture of an image of presented workpiece to the robot using a camera mounted on the robot assembly. Heping fails to teach or suggest reading a barcode that provides attachment instructions that explicitly define co-ordinates of a first position of the part for attaching a first hardware component.
The cited reference of Shinozaki (U.S. 9,649,790) discloses application of a curing adhesive to a region of an article using a robot (see abstract). Shinozaki fails to teach or suggest reading a barcode that provides attachment instructions that explicitly define co-ordinates of a first position of the part for attaching a first hardware component.
The cited reference of Ross (NPL) discloses that applying Autonomous robots for the purpose of furniture parts assembly is well known (see pg. 855, paragraphs 1-4). Ross fails to teach or suggest reading a barcode that provides attachment instructions that explicitly define co-ordinates of a first position of the part for attaching a first hardware component.
The cited reference of Okuyama (U.S. Pub 2002/0105296) discloses transforming the position of a moving object on the conveyer based on its coordinate system to a robot coordinate system. Further in paragraph 8 indicating use of a camera for determining orientation and position of objects on a conveyer is known (abstract & paragraphs 18, 24 and 32). Okuyama fails to teach or suggest reading a barcode that provides attachment instructions that explicitly define co-ordinates of a first position of the part for attaching a first hardware component.
10.	Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee.  Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
References Cited
11.	The art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Buhrer et al. (U.S. 5,961,722) discloses “Apparatus For Establishing Reference Coordinates For A Point On A Component”
NAKAMURA (U.S. Pub 2024/0109190) discloses “Robot Control, System, Robot Control Method, And Program”
Hiroyki Kobayashi, A new proposal for self-localization of mobile robot by self-contained 2D barcode landmark, 2012, IEEE, pgs. 2080-2083
Jong Hwan Beck et al., Vision based Distance Measurement System using Two-dimensional Barcode for Mobile Robot, 2017, IEEE, pgs. 1-4 (pdf)

APPLICANT REBUTTAL: REMARKS
/
ARGUMENTS
By the present amendment, the claims have been amended as follows:
Claim 1 has been amended to recite that the instructions provided by the barcode include "co- ordinates of a first position of the part for attaching a first hardware component" and that the computing unit is configured to "based on the dimensions, the orientation and the co-ordinates of the first position, locate the first position of the part to provide the first hardware component".
Support for these amendments can be found throughout the application as filed, specifically at previous claim 3, paragraphs [0091] and [0094] as well as FIGs. 2-5.
Claim 3 has been cancelled.
Claim 16 has been amended to correspond with amended claim 1.
The amendments to the claims have been made without prejudice and without acquiescing to any of the Examiner's objections. Applicant reserves the right to pursue any deleted or withdrawn subject matter in a further divisional, continuation or continuation-in-part application. No new matter has been entered by the present amendment and its entry is respectfully requested/The amendments do not contain new matter and their entry is respectfully requested.
The Office Action dated November 21, 2024 (hereinafter, the "Office Action") has been carefully considered. It is believed that the amendments submitted herewith and the following comments represent a complete response to the Examiner's rejections and place the present application in condition for allowance. Reconsideration is respectfully requested.
Claim Re
j
ections - 35 U.S.C.
§
Claims 1-10 and 12 have been rejected under 35 U.S.C. 103 as being unpatentable over Chen (U.S. 4,613,942, filed Oct. 22, 1984, hereinafter "Chen") in view of Heping (U.S. Pub. 2011/0087360, filed Mar. 30, 2009) further in view of Shinozaki (U.S. 9,649,790, filed Nov. 30, 2012, hereinafter "Shinozaki") further in view of Ross (NPL- IkeaBot: An Autonomous Multi- Robot Coordinated Furniture Assembly System, published May 2013, pgs. 855-862, hereinafter "Ross") further in view of Okuyama (U.S. Pub 2002/0105296, filed Dec. 21, 2001).
Claims 16, 20-21 and 23-28 have been rejected under 35 U.S.C. 103 as being unpatentable over Chen (U.S. 4,613,942, filed Oct. 22, 1984, hereinafter "Chen") in view of Heping (U.S. Pub. 2011/0087360, filed Mar. 30, 2009) further in view of Ross (NPL- IkeaBot: An Autonomous Multi-Robot Coordinated Furniture Assembly System, published May 2013, pgs. 855-862, hereinafter "Ross") further in view of Okuyama (U.S. Pub 2002/0105296, filed Dec. 21, 2001).
Applicant respectfully disagrees.
Notwithstanding the foregoing, as noted above, claim 1 has been amended to recite that the instructions provided by the barcode include "co-ordinates of a first position of the part for attaching a first hardware component" and that the computing unit is configured to "based on the dimensions, the orientation and the co-ordinates of the first position, locate the first position of the part to provide the first hardware component".
With regards to claim 1, Applicant notes that the Examiner asserts on page 4 of the Office Action that Chen teaches the claimed feature of "the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture" at "see fig.1, numeral 14 & col. 2, lines 45-65, discloses a camera for obtaining and processing a coded indica image on a part within its field of vision. Further supporting use of a bar code for the indica in col. 4, lines 35-67. The part is then used to perform an assembly operation by the robot arm has determined by the indica outlined in col. 3, lines 25-35 & abstract".
Applicant respectfully disagrees. In addition, Applicant submits that Chen does not teach or suggest the feature of the instructions provided by the barcode including "co-ordinates of a first position of the part for attaching a first hardware component".
Applicant submits that in Chen, col. 3, lines 25-35 teaches that the "fourth set of indicia 45 comprises a series of differently colored geometric shapes, e.g., 46, 47, 48,
which series identifies the operation which is to be performed by the robot arm with the part.
That is, the program for the computer is on the part itself, which program instructs the robot to perform the programmed operation as set forth by the indicia. [emphasis added].
Applicant then notes that, on page 7 of the Office Action, the Examiner alleges that col. 60, lines 3-5 "discloses that the indicia provide data associated with coordinates on the part to perform the assembly instructions."
Applicant respectfully disagrees.
Col. 60, lines 3-5 of Chen state "a part having random orientation, said part having orientation indicia on said part to provide three dimensional disposition data of said part". Read in the context of the entire application, the Applicant submits that the "orientation indicia" here are shapes, specifically a red triangle and a yellow dot at one apex of the triangle. The digital image processor of Chen recognizes the triangle, and the computer measures the altitude 115 of the triangle through dot 111, as well as the rotation of the triangle about dot 111. Other differently colored dots may be disposed at the other apices.
Applicant therefore submits that, in this portion of Chen, there is no teaching of "a barcode positioned on a part presented to the robot as the part rests on a conveyor, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture, the instructions including co-ordinates of a first position of the part for attaching a first hardware component".
More generally, it is clear from the above that in Chen the indicia is scanned to instruct the robot on how to use the part that is presented with the barcode. The robot is not provided with instructions of "co-ordinates
of
a first position of the part" as claimed in amended claim 1.
Chen does not teach or suggest receiving any "co-ordinates of a first position of the part" that is presented to the camera because Chen is not concerned with performing operations on the part. Rather, Chen is concerned with performing operations with the part that is presented. Chen therefore does not teach that the barcode provides "co-ordinates of a first position of the part for attaching a first hardware component" because Chen is only concerned with picking up and using the parts that are presented to the camera.
For the above foregoing reasons, claim 1 as amended is novel and inventive over Chen.
With respect to the remaining prior art noted by the Examiner, Applicant further notes that in the Office Action the Examiner further asserts on page 6 that Okuyama discloses, at the Abstract and paragraphs 18, 24 and 32,
transforming the position of a moving object on the conveyer based on its coordinate system to a robot coordinate system. Further, in paragraph 8 indicating use of a camera for determining orientation and position of objects on a conveyor is known); It would have been obvious for one or ordinary skill in the art before the effective filing date of the application to have modified camera placement by mounting the camera on the robot for capturing part details and barcode data in addition to implementing known techniques for calculating parts on a conveyer based on determined coordinate systems and applying
adhesives for part assembly"
Applicant respectfully disagrees.
Okuyama does not teach or suggest the claimed step of "determining co-ordinates of
a first
p
osition on the
p
art
to provide the first hardware component to the part" as alleged by the Examiner. Okuyama describes the use of a conveyor co-ordinate system to determine a position of a work on a conveyor and translate that position to a robot coordinate system. Nowhere does Okuyama teach identifying a first position on a part based on a camera capturing an image.
Further, claim 1 as amended now recites "a barcode positioned on a part presented to the robot as the part rests on a conveyor, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture, the instructions including co-ordinates of a first position of the part for attaching a first hardware component", which is also not taught in Okuyama.
Okuyama therefore does not correct the deficiencies of Chen.
Heping, Shinozaki and Ross also fail to correct the deficiencies of Chen as each reference also fails to teach or suggest at least "a barcode positioned on a part presented to the robot as the part rests on a conveyor, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture, the instructions including co-ordinates of a first position of the part for attaching a first hardware component".
Applicant therefore submits that none of the prior art cited by the Examiner teaches or suggests recites "a barcode positioned on a part presented to the robot as the part rests on a conveyor, the barcode providing instructions for attaching one or more hardware components to the part to assemble the piece of furniture, the instructions including co-ordinates of a first position of the part for attaching a first hardware component" as claimed in amended claim 1.
Therefore, claim 1 as amended is also novel and inventive over Chen in view of Heping, Shinozaki, Ross and Okuyama either alone or in combination.
Applicant submits that claims 4, 6-12 are therefore also novel and inventive over Chen in view of Shinozaki and further in view of Ross by way of their dependency on claim 1 as amended.
With respect to claims 16, 20-21 and 23-28, Applicant submits that claim 16 as amended corresponds with claim 1 as amended and therefore is novel and inventive over Chen in view of Heping, Shinozaki, Ross and Okuyama, either alone or in combination, for at least the same reasons as provided above in support of claim 1 as amended.
Claims 20-21 and 23-28 are therefore also novel and inventive over Chen in view of Heping, Shinozaki, Ross and Okuyama by way of their dependency on claim 16 as amended.
In view of the foregoing, Applicant respectfully submits that the claims, as amended, are non- obvious, and requests for this rejection under 35 U.S.C. § 103 to be withdrawn and that the claims, as amended, be allowed.
Conclusion


CITED REFERENCE SUMMARIES: Ref US20240109190A1: Claims:
A robot control system, comprising: a robot device; a work status sensor that acquires information indicating a work status of the robot device with respect to a workpiece; an arithmetic processing unit that estimates and outputs a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by the work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating the work status acquired by the work status sensor, the workpiece type, and the progress of the work process; at least one or more action pattern generation units that generate an action pattern of the robot device corresponding to the current work process; and an action selection unit that selects the action pattern generation unit on the basis of the workpiece type and the work process progress outputted by the arithmetic processing unit.
a work status sensor that acquires information indicating a work status of the robot device with respect to a workpiece;
an arithmetic processing unit that estimates and outputs a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by the work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating the work status acquired by the work status sensor, the workpiece type, and the progress of the work process;
at least one or more action pattern generation units that generate an action pattern of the robot device corresponding to the current work process; and
an action selection unit that selects the action pattern generation unit on the basis of the workpiece type and the work process progress outputted by the arithmetic processing unit.
The robot control system according to claim 1 , wherein the learning model is subjected to machine learning by means of the training data including the information indicating the work status acquired by the work status sensor, the workpiece type, the progress of the work process, and correctness of the work in the work process, and the learning model is configured to, when the information indicating a current work status acquired by the work status sensor is inputted, estimate the success or failure of the work in the work process in addition to the workpiece type and the progress of the current work process which are included in the information indicating the current work status, and wherein the action selection unit selects the action pattern generation unit on the basis of the workpiece type, the progress of the current work process, and the success/failure of the work in the work process, which are outputted by the arithmetic processing unit by using the learning model.
wherein the learning model is subjected to machine learning by means of the training data including the information indicating the work status acquired by the work status sensor, the workpiece type, the progress of the work process, and correctness of the work in the work process, and the learning model is configured to, when the information indicating a current work status acquired by the work status sensor is inputted, estimate the success or failure of the work in the work process in addition to the workpiece type and the progress of the current work process which are included in the information indicating the current work status, and
wherein the action selection unit selects the action pattern generation unit on the basis of the workpiece type, the progress of the current work process, and the success/failure of the work in the work process, which are outputted by the arithmetic processing unit by using the learning model.
The robot control system according to claim 2 , wherein, in a case where the action selection unit estimates that the work in the current work process has not been completed in the arithmetic processing unit, the action selection unit selects, from among the action pattern generation units, the action pattern generation unit which generates an action pattern for completing the work in the corresponding work process.
wherein, in a case where the action selection unit estimates that the work in the current work process has not been completed in the arithmetic processing unit, the action selection unit selects, from among the action pattern generation units, the action pattern generation unit which generates an action pattern for completing the work in the corresponding work process.
The robot control system according to claim 3 , wherein the action pattern for completing the work in the corresponding work process is an action pattern for performing the work to correct a work result according to an action pattern generated by the action pattern generation unit previously selected by the action selection unit.
wherein the action pattern for completing the work in the corresponding work process is an action pattern for performing the work to correct a work result according to an action pattern generated by the action pattern generation unit previously selected by the action selection unit.
The robot control system according to claim 1 , wherein the learning model is subjected to machine learning by means of training data that includes information indicating the work status acquired by the work status sensor, the workpiece type, respective work process types of a plurality of independent work processes, and the progress of each work process, and is configured such that, when information indicating a current work status acquired by the work status sensor is inputted, the learning model estimates the workpiece type, the types of the plurality of independent work processes, and the progress of each of the current work processes, which are included in the information indicating the current work status, and wherein the action selection unit selects the action pattern generation unit corresponding to an executable work process among the plurality of independent work processes on the basis of the workpiece type, the types of the plurality of independent work processes, and the progress of each of the current work processes, which are outputted by the arithmetic processing unit by using the learning model.
wherein the learning model is subjected to machine learning by means of training data that includes information indicating the work status acquired by the work status sensor, the workpiece type, respective work process types of a plurality of independent work processes, and the progress of each work process, and is configured such that, when information indicating a current work status acquired by the work status sensor is inputted, the learning model estimates the workpiece type, the types of the plurality of independent work processes, and the progress of each of the current work processes, which are included in the information indicating the current work status, and
wherein the action selection unit selects the action pattern generation unit corresponding to an executable work process among the plurality of independent work processes on the basis of the workpiece type, the types of the plurality of independent work processes, and the progress of each of the current work processes, which are outputted by the arithmetic processing unit by using the learning model.
The robot control system according to claim 5 , wherein the training data includes a priority of each work process in addition to the information indicating the work status acquired by the work status sensor, the workpiece type, the types of the respective work processes of the plurality of independent work processes, and the progress of each of the current work processes, and wherein the action selection unit selects the action pattern generation unit corresponding to a work process having a high priority.
wherein the training data includes a priority of each work process in addition to the information indicating the work status acquired by the work status sensor, the workpiece type, the types of the respective work processes of the plurality of independent work processes, and the progress of each of the current work processes, and
wherein the action selection unit selects the action pattern generation unit corresponding to a work process having a high priority.
The robot control system according to claim 1 , further comprising two or more robot devices on which different end effectors are mounted, wherein the action selection unit selects the action pattern generation unit corresponding to any of the two or more robot devices on the basis of the workpiece type and the progress of the current work process which are outputted by the arithmetic processing unit.
two or more robot devices on which different end effectors are mounted,
wherein the action selection unit selects the action pattern generation unit corresponding to any of the two or more robot devices on the basis of the workpiece type and the progress of the current work process which are outputted by the arithmetic processing unit.
The robot control system according to claim 1 , wherein the work status sensor is attached to the robot device and is an imaging device that captures an image including at least the workpiece as the information indicating the work status of the robot device.
wherein the work status sensor is attached to the robot device and is an imaging device that captures an image including at least the workpiece as the information indicating the work status of the robot device.
The robot control system according to claim 1 , wherein the robot device has a robot arm constituted by one or more joints, and an end effector.
wherein the robot device has a robot arm constituted by one or more joints, and an end effector.
A robot control system, comprising: an arithmetic processing unit that estimates and outputs a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by a work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating a work status of a robot device with respect to a workpiece acquired by the work status sensor, the workpiece type, and the progress of the work process; at least one or more action pattern generation units that generate an action pattern of the robot device corresponding to the current work process; and an action selection unit that selects the action pattern generation unit on the basis of the workpiece type and the progress of the current work process, which are outputted by the arithmetic processing unit.
an arithmetic processing unit that estimates and outputs a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by a work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating a work status of a robot device with respect to a workpiece acquired by the work status sensor, the workpiece type, and the progress of the work process;
an action selection unit that selects the action pattern generation unit on the basis of the workpiece type and the progress of the current work process, which are outputted by the arithmetic processing unit.
A robot control method, comprising the processing steps of: estimating and outputting a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by a work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating a work status of a robot device with respect to a workpiece acquired by the work status sensor, the workpiece type, and the progress of the work process; and selecting an action pattern generation unit from among at least one or more action pattern generation units that generate an action pattern of the robot device corresponding to the work process, on the basis of the estimated workpiece type and the estimated progress of the current work process.
estimating and outputting a workpiece type and progress of a current work process, which correspond to information indicating a current work status acquired by a work status sensor by using a learning model subjected to machine learning by means of training data which includes the information indicating a work status of a robot device with respect to a workpiece acquired by the work status sensor, the workpiece type, and the progress of the work process; and
selecting an action pattern generation unit from among at least one or more action pattern generation units that generate an action pattern of the robot device corresponding to the work process, on the basis of the estimated workpiece type and the estimated progress of the current work process.
Ref US5961722A: Claims:
Apparatus for establishing a reference coordinate for a point on a component, comprising: a component carriage configured to support a semiconductor wafer, said component carriage having coordinate indicia thereon; a locator plate movably supported relative to said component support carriage and having reference indicia thereon for registration with said component carriage.
a component carriage configured to support a semiconductor wafer, said component carriage having coordinate indicia thereon;
a locator plate movably supported relative to said component support carriage and having reference indicia thereon for registration with said component carriage.
The apparatus of claim 1 wherein said locator plate comprises a portion formed of transparent material.
The apparatus of claim 1 wherein said locator plate is movably supported above said component carriage.
The apparatus of claim 1 wherein said component carriage is movable relative to said locator plate along a first axis.
The apparatus of claim 4 wherein said locator plate is movable relative to said carriage along a second axis intersecting said first axis.
The apparatus of claim 1 wherein said coordinate indicia comprises numerical indicia and wherein said reference indicia comprises two intersecting lines on said locator plate.
The apparatus of claim 1 further comprising a base for movably supporting said component carriage along a first axis, said base movably supporting said locator plate for movement relative to said component carriage along a second axis intersecting said first axis.
The apparatus of claim 7 where in s aid base has a pair of first spaced-apart mounting rods attached thereto and wherein said component carriage is movably attached to said first spaced-apart mounting rods by first bearings attach ed to said component carriage, s aid first bearings slidably received on said first mounting rods for slidable travel thereon.
The apparatus of claim 8 wherein said base has a pair of second spaced-apart mounting rods attached thereto and wherein said locator plate is movably attached to said second spaced-apart rods by second bearings slidably received on said second mounting rods for slidable travel thereon.
Apparatus for establishing reference coordinates for a point on a component, comprising: a base; a component carriage configured to support a semiconductor wafer, said component carriage being movably attached to said base for movement relative thereto along a first axis; a locator plate movably attached to said base for movement relative thereto along a second axis that is perpendicular to said first axis; coordinate indicia on said component carriage; and reference indicia on said locator plate for registration with said component carriage.
a component carriage configured to support a semiconductor wafer, said component carriage being movably attached to said base for movement relative thereto along a first axis;
a locator plate movably attached to said base for movement relative thereto along a second axis that is perpendicular to said first axis;
coordinate indicia on said component carriage; and
reference indicia on said locator plate for registration with said component carriage.
The apparatus of claim 10 wherein said component carriage is constructed to support said wafer in a planar orientation relative to said locator plate.
The apparatus of claim 10 wherein said component carriage movably supports said wafer in a first plane and wherein said locator plate is movable along a second plane that is parallel to said first plane.
The apparatus of claim 12 wherein said locator plate is movably supported above said component carriage and is formed of transparent material.
Apparatus for establishing reference coordinates for a point on a semiconductor wafer, comprising: a base; a wafer carriage configured to support a semiconductor wafer, said carriage being movably attached to said base for movement along a first plane; a transparent locator plate movably attached to said base for movement along a second plane that is parallel to said first plane; coordinate indicia on said wafer carriage; reference indicia on said locator plate for registration with a point on wafer supported on said wafer carriage and alignment with said coordinate indicia on said wafer support carriage.
a wafer carriage configured to support a semiconductor wafer, said carriage being movably attached to said base for movement along a first plane;
a transparent locator plate movably attached to said base for movement along a second plane that is parallel to said first plane;
coordinate indicia on said wafer carriage;
reference indicia on said locator plate for registration with a point on wafer supported on said wafer carriage and alignment with said coordinate indicia on said wafer support carriage.
Apparatus for establishing at least one reference coordinate for a point on a semiconductor wafer, said apparatus comprising: a semiconductor wafer carriage movable in a first plane and having coordinate indicia thereon; and a locator plate movable in a second plane above said first plane and having referencing indicia thereon.
a semiconductor wafer carriage movable in a first plane and having coordinate indicia thereon; and
a locator plate movable in a second plane above said first plane and having referencing indicia thereon.
The apparatus of claim 15 wherein said semiconductor wafer carriage is movable in said first plane in directions defined by a first axis and wherein said locator plate is movable in said second plane in directions defined by a second axis that is substantially perpendicular to said first axis.
The apparatus of claim 16 wherein said coordinate indicia is on a first numerical scale affixed to said semiconductor wafer carriage and a second numerical scale affixed to said semiconductor wafer carriage substantially perpendicular to said first numerical scale.
The apparatus of claim 17 wherein said referencing indicia comprises: a first line corresponding to said first numerical scale; and a second line intersecting said first line and corresponding to said second numerical scale.
a first line corresponding to said first numerical scale; and
a second line intersecting said first line and corresponding to said second numerical scale.
Ref US4613942: Claims:
1. An orientation and control system for robots comprising:a random oriented part having coded indicia being digital image processor recognizable; a camera being positioned so as to view the coded indicia, a digital image processor interconnected to said camera for recognizing the indicia image and further comprising a computer for decoding the indicia so as to provide an x y z axes orientation input signal; a robot having an arm for performing an operation with said part, said robot arm having coded indicia operatively associated therewith, said robot indicia being viewable by said camera and said ro
[Truncated to input limit]