DETAILED ACTION
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.
Claim Rejections - 35 USC § 103
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.
Claims 1-4, 6-8, and 12-18 are rejected under 35 U.S.C. 103 as being unpatentable over
U.S. Patent Application Publication No. 2007/0010898 (Hosek) in view of
U.S. Patent Application Publication No. 2022/0227379 (Robinson).
Claim 1:
The cited prior art describes a control system for controlling a device operative to perform an operation on a workpiece based on a spatial relationship between the device and the workpiece, wherein the spatial relationship is adjustable using at least one actuator, the control system comprising: (Hosek: see the control system 100 as illustrated in figure 1 and as described in paragraph 0080; “The axes may be part of one or more complex multi-axis non-linear machines, for example, a system of precision robots.” Paragraph 0080; “The robots 510, 520 may be five axis machines with complex non-linear dynamics while the aligners 515, 525 may be two axis machines. In this example, the robots 510, 520 pick substrates 530, 535 from designated locations and place them on aligners 525, 515, respectively. The aligners 525, 515 may scan the substrates 530, 535 for eccentricity and alignment features. After scanning, the robots 510, 520 may pick the substrates 530, 535 and place them elsewhere. In one embodiment, the work cell 505 may be part of the clustered architecture control system 100 (FIG. 1).” Paragraph 0113)
a primary node controller communicatively coupled to the device, wherein the primary node controller is adapted to control an operation of the device; and (Hosek: see the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081; “The clustered architecture control system 100 may also include at least one bridge node 135 which allows the master controller to communicate with nodes on another communication network, such as a controller area network (CAN). The control system may then be able to control CAN based modules and components, for example, CAN axis controllers, grippers, doors, actuators, sensors, etc.” paragraph 0081)
at least one secondary node controller communicatively coupled to the primary node controller, wherein the at least one secondary node controller is adapted to: (Hosek: see the cluster controllers 110 as illustrated in figure 1 and as described in paragraphs 0079, 0080; “The clustered architecture control system 100 includes a master controller 105, one or more cluster controllers 110, one or more remote controllers 115, and one or more autonomous remote controllers 150 connected together through a communication network 120.” Paragraph 0079)
receive encoder feedback from the at least one actuator, the encoder feedback representing a position of a mechanical load associated with an actuator of the at least one actuator; (Hosek: “The autonomous remote controller 150 may also read feedback signals such as position information from a feedback device 145, for example, an encoder and current draw from the axis 125 and convey those to the master controller 105.” Paragraph 0083; “Encoder 145 may provide remote controller 115 with raw position information such as a number of encoder counts or steps, an angle measurement, etc. from which remote controller 115 may compute actual position information.” Paragraph 0107; “The autonomous remote controllers 150 may use the trajectory data in real time control algorithms to produce control actions such as applying power to axis actuators 140, and may also convey status information to the master controller 105.” Paragraph 0084; “Remote controllers 1230, 1235, 1240 may capture certain characteristics, such as the positions and velocities of each axis of the robot 1210, and provide the data to master controller 1245.” Paragraph 0181)
Hosek does not explicitly describe the combination of encoding and decoding data as described below. However, Robinson teaches the combination of encoding and decoding data as described below.
perform a data compression algorithm on the encoder feedback to encode the encoder feedback; (Hosek: see the interpolate data 1340 (i.e., data compression) as illustrated in figure 13; “The specified nodes interpolate their buffered quantities of interest to determine a value for the quantities at the event time as shown in block 1340.” Paragraph 0185) (Robinson: “encode the one or more sensor measurements to compress the one or more sensor measurements by mapping the one or more sensor measurements onto latent space for the node to form encoded sensor data” paragraph 0066; “The embodiments described herein compress sensor data by encoding the sensor data using specifically trained encoders. The compression reduces the amount of data sent to, and optimises the data for, the machine learning system.” Paragraph 0082)
generate a plurality of data packets representing the encoder feedback and transmit the plurality of data packets, (Hosek: see the send data to master controller 1345 as illustrated in figure 13 and as described in paragraph 0185; “The specified nodes send the interpolated values of the quantities of interest to the master controller as shown in block 1345.” Paragraph 0185) (Robinson: “send the encoded sensor data to a parent node for combination with further encoded sensor data from one or more other sensors of the plurality of sensors” paragraph 0066; “The encoded data E.sub.1, E.sub.2 from each node is sent to the fusion node 30 which occupies a second level within the network.” Paragraph 0098)
wherein the primary node controller is further adapted to: (Hosek: see the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081)
receive the plurality of data packets, (Hosek: see the data values received by the master controller as illustrated in figure 13)
decode the plurality of data packets as a plurality of decoded data packets, and (Robinson: “The decoder of the fusion node 30 can decode the combined encoded data C.sub.1 to produce corresponding predications E.sub.1′, E.sub.2′ of the encoded sensor data E.sub.1, E.sub.2 from the first 10 and second 20 nodes. . . Alternatively, this may be achieved through the fusion node 30 implementing copies of the decoders 14, 24 of the sensor nodes 10, 20. The fusion node itself may therefore be able to decode the predicted encoded sensor data to produce predicted sensor data.” Paragraph 0099)
control an operation of the device based, at least in part, on the plurality of decoded data packets. (Hosek: see the alter trajectories or operation 1350 as illustrated in figure 13 and as described in paragraph 0185; “The master controller 1245 may then determine the position of the robot's end-effector 1220 as the payload edges are detected, and then determine the actual location of the center of the payload 1205. Once the payload center is determined, the master controller 1245 may alter the trajectory of the robot 1210 so that the payload 1205 is delivered in a centered manner regardless of the amount and direction of the initial eccentricity.” Paragraph 0181)
One of ordinary skill in the art would have recognized that applying the known technique of Hosek, namely, a motion control system, with the known techniques of Robinson, namely, training autonomous control systems, would have yielded predictable results and resulted in an improved system. Accordingly, applying the teachings of Hosek to use various controllers and communication therebetween to control a motion control system with the teachings of Robinson to communicate sensor data between components of the control system would have been recognized by those of ordinary skill in the art as resulting in an improved control and communication system. In other words, the combination of the references provides for a control system that communicates data between control components using various communication techniques based on the teachings of a control system that communicates data between control components in Hosek and the teachings of communicating data between control components using various communication techniques in Robinson).
Claim 2:
The cited prior art describes the control system of claim 1, further comprising the device. (Hosek: see sensor connected to the bridge node 135 for communication with the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081; “The clustered architecture control system 100 may also include at least one bridge node 135 which allows the master controller to communicate with nodes on another communication network, such as a controller area network (CAN). The control system may then be able to control CAN based modules and components, for example, CAN axis controllers, grippers, doors, actuators, sensors, etc.” paragraph 0081)
Claim 3:
The cited prior art describes the control system of claim 2, wherein the device includes at least one selected from the group consisting of a laser and a sensor. (Hosek: see sensor connected to the bridge node 135 for communication with the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081; “The clustered architecture control system 100 may also include at least one bridge node 135 which allows the master controller to communicate with nodes on another communication network, such as a controller area network (CAN). The control system may then be able to control CAN based modules and components, for example, CAN axis controllers, grippers, doors, actuators, sensors, etc.” paragraph 0081)
Claim 4:
The cited prior art describes the control system of claim 1, further comprising the at least one actuator. (Hosek: see the actuators 140 as illustrated in figure 1 and as described in paragraphs 0083, 0084; “The remote controllers managed by the cluster controller 110 may, for example, apply power to axis actuators 140 in response to the torque commands, and may also convey axis information, such as actual positions, to the cluster controller 110.” Paragraph 0085)
Claim 6:
The cited prior art describes the control system of claim 4, wherein the at least one actuator is mechanically coupled to the workpiece. (Hosek: see the robots 510, 520 and aligners 515, 525 connected to the controllers 555, 560, 585, 590, 570, 575 as illustrated in figure 5a)
Claim 7:
The cited prior art describes the control system of claim 1, further comprising a plurality of secondary node controllers. (Hosek: see the cluster controllers 110 as illustrated in figure 1 and as described in paragraphs 0079, 0080; “The clustered architecture control system 100 includes a master controller 105, one or more cluster controllers 110, one or more remote controllers 115, and one or more autonomous remote controllers 150 connected together through a communication network 120.” Paragraph 0079)
Claim 8:
The cited prior art describes the control system of claim 7, further comprising a plurality of actuators. (Hosek: see the actuators 140 as illustrated in figure 1 and as described in paragraphs 0083, 0084; “The remote controllers managed by the cluster controller 110 may, for example, apply power to axis actuators 140 in response to the torque commands, and may also convey axis information, such as actual positions, to the cluster controller 110.” Paragraph 0085)
Claim 12:
Claim 12 is substantially similar to claims 1 and 4 and is rejected based on the same reasons and rationale.
12. A motion system, comprising;
a first actuator; and
a control system for controlling a device to perform an operation on a workpiece based on a spatial relationship between the device and the workpiece, wherein the spatial relationship is adjustable using the first actuator, the control system comprising:
a primary node controller communicatively coupled to the first actuator, wherein the primary node controller is adapted to control an operation of the device; and
at least one secondary node controller communicatively coupled to the primary node controller, wherein the at least one secondary node controller is adapted to:
receive encoder feedback from the first actuator, the encoder feedback representing a position of a mechanical load associated with the first actuator;
perform a data compression algorithm on the encoder feedback to encode the encoder feedback;
generate a plurality of data packets representing the encoder feedback and transmit the plurality of data packets,
wherein the primary node controller is further adapted to:
receive the plurality of data packets,
decode the plurality of data packets as a plurality of decoded data packets, and
control an operation of the device based, at least in part, on the plurality of decoded data packets.
Claim 13:
Claim 13 is substantially similar to claim 4 and is rejected based on the same reasons and rationale.
13. The motion system of claim 12, further comprising at least one second actuator.
Claim 14:
Claim 14 is substantially similar to claim 3 and is rejected based on the same reasons and rationale.
14. The motion system of claim 12, wherein the device includes at least one selected from the group consisting of a laser and a sensor.
Claim 15:
The cited prior art describes the motion system of claim 12, further comprising a plurality of secondary node controllers and a plurality of actuators, wherein each of the plurality of actuators is associated with a respective secondary node controller of the plurality of secondary node controllers. (Hosek: see the cluster controllers 110 with associated actuators 140 as illustrated in figure 1 and as described in paragraphs 0079, 0080; “The clustered architecture control system 100 includes a master controller 105, one or more cluster controllers 110, one or more remote controllers 115, and one or more autonomous remote controllers 150 connected together through a communication network 120.” Paragraph 0079; “The autonomous remote controller 150 may use the torque commands to produce control actions such as applying voltage to an axis actuator 140, for example, a motor.” Paragraph 0083)
Claim 16:
Claim 16 is substantially similar to claim 1 and is rejected based on the same reasons and rationale.
16. A non-transitory computer-readable medium for use with a control system, having a memory which, when executed by the control system, causes the control system to:
control a device operative to perform an operation on a workpiece based on a spatial relationship between the device and the workpiece, wherein the spatial relationship is adjustable using at least one actuator, wherein the control system comprises:
a primary node controller communicatively coupled to the device, wherein the primary node controller is adapted to control an operation of the device; and
at least one secondary node controller communicatively coupled to the primary node controller, wherein the at least one secondary node controller is adapted to:
receive encoder feedback from the at least one actuator, the encoder feedback representing a position of a mechanical load associated with an actuator of the at least one actuator;
perform a data compression algorithm on the encoder feedback to encode the encoder feedback;
generate a plurality of data packets representing the encoder feedback and transmit the plurality of data packets,
wherein the primary node controller is further adapted to:
receive the plurality of data packets,
decode the plurality of data packets as a plurality of decoded data packets, and
control an operation of the device based, at least in part, on the plurality of decoded data packets.
Claim 17:
Claim 17 is substantially similar to claim 7 and is rejected based on the same reasons and rationale.
17. The non-transitory computer-readable medium of claim 16, further comprising a plurality of secondary node controllers.
Claim 18:
Claim 18 is substantially similar to claim 8 and is rejected based on the same reasons and rationale.
18. The control system of claim 17, further comprising a plurality of actuators.
Claims 5 and 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over
U.S. Patent Application Publication No. 2007/0010898 (Hosek) in view of
U.S. Patent Application Publication No. 2022/0227379 (Robinson) and further in view of
U.S. Patent Application Publication No. 2012/0095599 (Pak).
Claim 5:
Hosek and Robinson do not explicitly describe a linear actuator as described below. However, Pak teaches the linear actuator as described below.
The cited prior art describes the control system of claim 4, wherein the at least one actuator includes a linear actuator. (Pak: “In this case, a second linear actuator provides motion in the axial direction, parallel to the spindle axis of rotation.” Paragraph 0043; “In another alternate implementation, the workpiece is placed on a Cartesian stage comprised of stacked perpendicular standard linear actuators, permitting the workpiece to be moved in a plane.” Paragraph 0045)
One of ordinary skill in the art would have recognized that applying the known technique of Hosek, namely, a motion control system, with the known techniques of Robinson, namely, training autonomous control systems, and the known techniques of Pak, namely, a machine control system, would have yielded predictable results and resulted in an improved system. Accordingly, applying the teachings of Hosek to use various controllers and communication therebetween to control a motion control system with the teachings of Robinson to communicate sensor data between components of the control system and the teachings of Pak to utilize various components in a machine control system would have been recognized by those of ordinary skill in the art as resulting in an improved control and communication system. In other words, the combination of the references provides for a control system that communicates data between control components using various communication techniques and various hardware components based on the teachings of a control system that communicates data between control components in Hosek and the teachings of communicating data between control components using various communication techniques in Robinson and the teachings of machine control using linear actuators and lasers in Pak.
Claim 9:
The cited prior art describes a system, comprising; (Hosek: see the control system 100 as illustrated in figure 1 and as described in paragraph 0080; “The axes may be part of one or more complex multi-axis non-linear machines, for example, a system of precision robots.” Paragraph 0080; “The robots 510, 520 may be five axis machines with complex non-linear dynamics while the aligners 515, 525 may be two axis machines. In this example, the robots 510, 520 pick substrates 530, 535 from designated locations and place them on aligners 525, 515, respectively. The aligners 525, 515 may scan the substrates 530, 535 for eccentricity and alignment features. After scanning, the robots 510, 520 may pick the substrates 530, 535 and place them elsewhere. In one embodiment, the work cell 505 may be part of the clustered architecture control system 100 (FIG. 1).” Paragraph 0113)
Hosek does not explicitly describe the combination of encoding and decoding data or a laser as described below. However, Robinson teaches the combination of encoding and decoding data and Pak teaches the laser as described below.
a laser configured emit a laser pulse propagating along a propagation path to irradiate a workpiece; (Pak: see the laser 510 directed a beam onto a stage 550 with a workpiece as illustrated in figures 5A, 5B, 5C and as described in paragraph 0045)
at least one actuator configured to support the workpiece; and (Hosek: see the actuators 140 as illustrated in figure 1 and as described in paragraphs 0083, 0084; “The remote controllers managed by the cluster controller 110 may, for example, apply power to axis actuators 140 in response to the torque commands, and may also convey axis information, such as actual positions, to the cluster controller 110.” Paragraph 0085)
a control system for controlling the laser to emit the pulse based on a spatial relationship between the propagation path and the workpiece, wherein the spatial relationship is adjustable using the at least one actuator, (Hosek: see the control system 100 as illustrated in figure 1 and as described in paragraph 0080; “The axes may be part of one or more complex multi-axis non-linear machines, for example, a system of precision robots.” Paragraph 0080; “The robots 510, 520 may be five axis machines with complex non-linear dynamics while the aligners 515, 525 may be two axis machines. In this example, the robots 510, 520 pick substrates 530, 535 from designated locations and place them on aligners 525, 515, respectively. The aligners 525, 515 may scan the substrates 530, 535 for eccentricity and alignment features. After scanning, the robots 510, 520 may pick the substrates 530, 535 and place them elsewhere. In one embodiment, the work cell 505 may be part of the clustered architecture control system 100 (FIG. 1).” Paragraph 0113) (Pak: see the controller 200 as illustrated in figure 2 and as described in paragraphs 0034, 0037; see the laser 510 directed a beam onto a stage 550 with a workpiece as illustrated in figures 5A, 5B, 5C and as described in paragraph 0045)
the control system comprising:
a primary node controller communicatively coupled to the laser, wherein the primary node controller is adapted to control an operation of the laser; and (Hosek: see the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081; “The clustered architecture control system 100 may also include at least one bridge node 135 which allows the master controller to communicate with nodes on another communication network, such as a controller area network (CAN). The control system may then be able to control CAN based modules and components, for example, CAN axis controllers, grippers, doors, actuators, sensors, etc.” paragraph 0081) (Pak: see the controller 200 as illustrated in figure 2 and as described in paragraphs 0034, 0037; see the laser 510 directed a beam onto a stage 550 with a workpiece as illustrated in figures 5A, 5B, 5C and as described in paragraph 0045)
at least one secondary node controller communicatively coupled to the primary node controller, wherein the at least one secondary node controller is adapted to: (Hosek: see the cluster controllers 110 as illustrated in figure 1 and as described in paragraphs 0079, 0080; “The clustered architecture control system 100 includes a master controller 105, one or more cluster controllers 110, one or more remote controllers 115, and one or more autonomous remote controllers 150 connected together through a communication network 120.” Paragraph 0079)
receive encoder feedback from the at least one actuator, the encoder feedback representing a position of a mechanical load associated with the at least one actuator; (Hosek: “The autonomous remote controller 150 may also read feedback signals such as position information from a feedback device 145, for example, an encoder and current draw from the axis 125 and convey those to the master controller 105.” Paragraph 0083; “Encoder 145 may provide remote controller 115 with raw position information such as a number of encoder counts or steps, an angle measurement, etc. from which remote controller 115 may compute actual position information.” Paragraph 0107; “The autonomous remote controllers 150 may use the trajectory data in real time control algorithms to produce control actions such as applying power to axis actuators 140, and may also convey status information to the master controller 105.” Paragraph 0084; “Remote controllers 1230, 1235, 1240 may capture certain characteristics, such as the positions and velocities of each axis of the robot 1210, and provide the data to master controller 1245.” Paragraph 0181)
perform a data compression algorithm on the encoder feedback to encode the encoder feedback; (Hosek: see the interpolate data 1340 (i.e., data compression) as illustrated in figure 13; “The specified nodes interpolate their buffered quantities of interest to determine a value for the quantities at the event time as shown in block 1340.” Paragraph 0185) (Robinson: “encode the one or more sensor measurements to compress the one or more sensor measurements by mapping the one or more sensor measurements onto latent space for the node to form encoded sensor data” paragraph 0066; “The embodiments described herein compress sensor data by encoding the sensor data using specifically trained encoders. The compression reduces the amount of data sent to, and optimises the data for, the machine learning system.” Paragraph 0082)
generate a plurality of data packets representing the encoder feedback and transmit the plurality of data packets, (Hosek: see the send data to master controller 1345 as illustrated in figure 13 and as described in paragraph 0185; “The specified nodes send the interpolated values of the quantities of interest to the master controller as shown in block 1345.” Paragraph 0185) (Robinson: “send the encoded sensor data to a parent node for combination with further encoded sensor data from one or more other sensors of the plurality of sensors” paragraph 0066; “The encoded data E.sub.1, E.sub.2 from each node is sent to the fusion node 30 which occupies a second level within the network.” Paragraph 0098)
wherein the primary node controller is further adapted to: (Hosek: see the master controller 105 as illustrated in figure 1 and as described in paragraphs 0079, 0080, 0081)
receive the plurality of data packets, (Hosek: see the data values received by the master controller as illustrated in figure 13)
decode the plurality of data packets as a plurality of decoded data packets, and (Robinson: “The decoder of the fusion node 30 can decode the combined encoded data C.sub.1 to produce corresponding predications E.sub.1′, E.sub.2′ of the encoded sensor data E.sub.1, E.sub.2 from the first 10 and second 20 nodes. . . Alternatively, this may be achieved through the fusion node 30 implementing copies of the decoders 14, 24 of the sensor nodes 10, 20. The fusion node itself may therefore be able to decode the predicted encoded sensor data to produce predicted sensor data.” Paragraph 0099)
control an operation of the laser based, at least in part, on the plurality of decoded data packets. (Hosek: see the alter trajectories or operation 1350 as illustrated in figure 13 and as described in paragraph 0185; “The master controller 1245 may then determine the position of the robot's end-effector 1220 as the payload edges are detected, and then determine the actual location of the center of the payload 1205. Once the payload center is determined, the master controller 1245 may alter the trajectory of the robot 1210 so that the payload 1205 is delivered in a centered manner regardless of the amount and direction of the initial eccentricity.” Paragraph 0181)
Hosek, Robinson, and Pak are combinable for the same rationale as set forth above with respect to claim 5.
Claim 10:
The cited prior art describes the control system of claim 9, further comprising a plurality of secondary node controllers. (Hosek: see the cluster controllers 110 as illustrated in figure 1 and as described in paragraphs 0079, 0080; “The clustered architecture control system 100 includes a master controller 105, one or more cluster controllers 110, one or more remote controllers 115, and one or more autonomous remote controllers 150 connected together through a communication network 120.” Paragraph 0079)
Claim 11:
The cited prior art describes the control system of claim 10, further comprising a plurality of actuators. (Hosek: see the actuators 140 as illustrated in figure 1 and as described in paragraphs 0083, 0084; “The remote controllers managed by the cluster controller 110 may, for example, apply power to axis actuators 140 in response to the torque commands, and may also convey axis information, such as actual positions, to the cluster controller 110.” Paragraph 0085)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication No. 2014/0025191 describes an apparatus for numerically controlled workpiece processing apparatus.
U.S. Patent Application Publication No. 2021/0291310 describes a direct pose feedback controlled machine with a laser measuring device.
U.S. Patent Application Publication No. 2020/0166913 describes a scalable motion control system.
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/Christopher E. Everett/Primary Examiner, Art Unit 2117
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