DETAILED CORRESPONDENCE
This action is in response to the filing of the Amendments on 06/19/2026. The amendments made have overcome the 112 rejection and the drawing objection.
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 .
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.
Claim(s) 1, 2, 3 7, 8, 11 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Adelson (US 20240025039) in view of Chu (US 20210379758) and Zeng (US 20230130977).
Claim 1, Adelson discloses a system for estimating properties of an object, comprising: a multi-finger end effector configured for performing one or more action sequences in a three-dimensional space to interact with multiple target contact points on the object and sensing tactile signals from the multiple target contact points [see Fig 1, p0030 – p0036];
an information processing unit including:
a property estimator configured for estimating the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector and the one
or more action sequences performed by the multi-finger end effector [see Adelson p0035 – p0036, p0039 - teaching one example of such a tactile sensor is an elastomeric tactile sensor available from Gelsight, Inc., of Waltham Massachusetts, which uses nonlinear properties of polydimethylsiloxane to sense forces on the sensors. Details of this sensor may be found in Yuan, Wenzhen, Siyuan Dong, and Edward H. Adelson, “Gelsight: High-resolution robot tactile sensors for estimating geometry and force,” (Sensors 17, no. 12 (2017): incorporated herein by reference. Generally, the surface of the elastomer deforms when forces are applied to it; Tilting the object to different angles provides information about the mass and center of mass. For example, at a low angle the measurements generally relate to mass of the object, while at a larger angle, the measurements provide information about the torque being applied to the sensor. Combining mass in torque estimates together provides information about the center of mass];
and
Adelson does not specifically teach an action selector configured for selecting the one or more action sequences to be performed by the multi-finger end effector on basis of prior information of the object and one or more properties to be estimated; and generating action command to the multi-finger end effector; and a data management unit configured for storing a pool of action sequences available to be selected by the action selector, the prior information of the object, the one or more properties to be estimated, the one or more action sequence performed by the multi-finger end effector and the one or more properties of the object estimated by the property estimator; wherein the tactile signals sensed from each contact point include signals indicative of a normal component and one or more tangential components of a contact force applied by the tactile sensor on the contact point; wherein the one or more action sequences include a tangential action sequence that causes at least two fingers of the multi-finger end effector to apply opposing tangential force components at different target contact points of the object; and wherein the property estimator is configured to estimate at least one material or mechanical property of the object based on the tactile signals including the opposing tangential force components and the one or more action sequences.
However, Chu discloses a method includes: obtaining, via a set of sensors, a representation of an environment; identifying a plurality of markers in the representation of the environment, each marker from the plurality of markers associated with a physical object from a plurality of physical objects located in the environment; an end effector with tactile sensors 357 disposed on the end of the end effectors which can measure the object in an environment. Further disclosing, robotic device 400 can engage in adaptive sensing where sensing can be performed based on stored knowledge and/or a user input. For example, robotic device 400 can identify an area in the environment to scan for an object based on prior information that is has on the object [see p0084, p0101].
Chu further discloses, a data management unit configured for storing a pool of action sequences available to be selected by the action selector, the prior information of the object, the one or more properties to be estimated, the one or more action sequence performed by the multi-finger end effector and the one or more properties of the object estimated by the property estimator; wherein the tactile signals sensed from each contact point include signals indicative of a normal component and one or more tangential components of a contact force applied by the tactile sensor on the contact point [see p0062 – p0063, p0070 for force applied by tactile sensors; p0078 – algorithms for machine learning, p0084, Fig 12 and p0144].
Therefore, it would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include an action selector configured for selecting the one or more action sequences to be performed by the multi-finger end effector on basis of prior information of the object and one or more properties to be estimated; and generating action command to the multi-finger end effector; and a data management unit configured for storing a pool of action sequences available to be selected by the action selector, the prior information of the object, the one or more properties to be estimated, the one or more action sequence performed by the multi-finger end effector and the one or more properties of the object estimated by the property estimator; wherein the tactile signals sensed from each contact point include signals indicative of a normal component and one or more tangential components of a contact force applied by the tactile sensor on the contact point, as suggested and taught by Chu, with a reasonable expectation of success, for the purpose of providing robotic systems that can perceive and adapt to dynamic and unstructured environments, and can perform tasks within those environments, without relying on pre-programmed manipulation skills.
Neither Adelson nor Chu specifically disclose wherein the one or more action sequences include a tangential action sequence that causes at least two fingers of the multi-finger end effector to apply opposing tangential force components at different target contact points of the object; and wherein the property estimator is configured to estimate at least one material or mechanical property of the object based on the tactile signals including the opposing tangential force components and the one or more action sequences.
However, Zeng discloses a robotic end effector that can be used in a variety of fields, such as robot grinding, assembly operations, human body massage, and rehabilitation services, and many more that require force control and position control of robot when handling an object.
Zeng teaches the object has a working surface, see Figs 4 and 5 which the end effector first establishes contact with, see Step 101, Fig, 2 - establish a steady state between the end effector and a working surface through a preset impedance control mechanism, and adjusting a contact force between the end effector and the working surface according to a preset desired force [see p0019]. At Step 104 – control the end effector to move tangentially along a working surface is provided, which requires both fingers or end effector units to apply opposing tangential force to the object [see p0032, Figs 4 – 6].
Zeng also discloses the following operation: establishing a steady state between the end effector and a working surface through a preset impedance control mechanism, and adjusting a contact force between the end effector and the working surface according to a preset desired force; obtaining a contact torque generated by the contact force; controlling the end effector to rotate according to the contact torque until a pose of the end effector is consistent with a pose of the working surface; and controlling the end effector to move tangentially along the working surface. With the method above, even in the face of an unknown working environment, the contact force can be effectively adjusted, and a task trajectory planning that adapts to the environment pose can be performed, thereby effectively reducing the error of the contact force [see p0036].
Additionally, see Fig. 6 the tangential motion control module 504 controls the end effector to move tangentially along the working surface of the object. Since this method is used in a variety of fields, applying Zeng method of tangential force can help establish mechanical properties of the working object [see p0003].
Therefore, it would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson as modified by Chu to include wherein the one or more action sequences include a tangential action sequence that causes at least two fingers of the multi-finger end effector to apply opposing tangential force components at different target contact points of the object; and wherein the property estimator is configured to estimate at least one material or mechanical property of the object based on the tactile signals including the opposing tangential force components and the one or more action sequences, as suggested and taught by Zeng, with a reasonable expectation of success, for the purpose of providing stability in an unknown working environment, or risk resulting in the inability to achieve effective adjustment of contact force. On the other hand, due to the unknown environment pose in task trajectory planning, it may cause a large contact force error when the planned trajectory cannot adapt to the environment pose, as tangentially moving end effectors avoid contact force errors.
Claim 11 is similarly rejected as Claim 1, see above.
Claim 2, as best understood, see 112 above, Adelson discloses the system according to claim 1, wherein one or more tangential components include a first tangential component, and a second tangential component orthogonal to the first tangential component [the Examiner interprets the first and second tangential components to be the end effector having two fingers (a first and second tangential component), See Adelson, Fig 1, (146 – end effector two prongs)].
Claim 3, Adelson discloses the system according to claim 1, but does not specifically teach further comprising a user interface allowing a user to input the prior information of the object and the one or more properties to be estimated; and wherein the data management unit is further configured to store the input prior information of the object and the one or more properties to be estimated.
However, Chu discloses displaying to a user the trajectory for the manipulating element in the representation of the environment; receiving, after the displaying, an input from the user; and in response to the input indicating an acceptance of the trajectory for the manipulating element, implementing the movements of the manipulating element (e.g., plurality of joints, end effector, transport element) to execute the physical interaction [p0018, p0054]. Further disclosing, robotic device 400 can engage in adaptive sensing where sensing can be performed based on stored knowledge and/or a user input. For example, robotic device 400 can identify an area in the environment to scan for an object based on prior information that is has on the object; Skill model(s) 334 are models that have been generated for performing different actions, and represent skills that have been learned by a robotic device. In some embodiments, each model 334 is associated with a set of markers that are tied to different physical objects in an environment [see Fig. 3, p0079, p0084, p0101, p0136].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include comprising a user interface allowing a user to input the prior information of the object and the one or more properties to be estimated; and wherein the data management unit is further configured to store the input prior information of the object and the one or more properties to be estimated, as suggested and taught by Chu, with a reasonable expectation of success, for the purpose of providing robotic systems that can perceive and adapt to dynamic and unstructured environments, and can perform tasks within those environments, without relying on pre-programmed manipulation skills.
Claim 7, as best understood, see 112 above, Adelson discloses the system according to claim 1, but is silent to further comprising one or more thermal sensors for collecting thermal information of the object; and wherein the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector and the collected thermal information.
However, Chu discloses, See Fig 4, a manipulating element 350, according to some embodiments. Manipulating element 350 can form a part of a robotic device, such as, for example, robotic device 102 and/or 200. Manipulating element 350 can be implemented as an arm that includes two or more segments 352 coupled together via joints 354. A plurality of sensors 353, 355, 357, and 358 can be disposed on different components of manipulating element 350, e.g., segments 352, joints 354, and/or end effector 356. Sensors 353, 355, 357, and 358 can be configured to measure sensory information, including environmental information and/or manipulating element information. Examples of sensors include position encoders, torque and/or force sensors, touch and/or tactile sensors, image capture devices such as cameras, temperature sensors, pressure sensors, light sensors, etc. Skill model(s) 334 are models that have been generated for performing different actions, and represent skills that have been learned by a robotic device. In some embodiments, each model 334 is associated with a set of markers that are tied to different physical objects in an environment. Marker information 335 can indicate which markers are associated with a particular model 334. Each model 334 can also be associated with sensory information 336 that is collected, e.g., via one or more sensors of a robotic device, during kinesthetic teaching and/or other demonstrations of a skill [see Fig 4, p0062, p0070, p0082 – p0084].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include comprising one or more thermal sensors for collecting thermal information of the object; and wherein the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector and the collected thermal information, as suggested and taught by Chu, with a reasonable expectation of success, for the purpose of providing sensors that capture information about the environment and/or objects in the environment around robotic device. The sensory information associated with the manipulating element, where the motion of the manipulating element is associated with a physical interaction between the manipulating element and the set of physical objects, ensuring safety and given certainty in a dynamic environment.
Claim 15 is similarly rejected as Claim 7, see above.
Claim 8, Adelson discloses the system according to claim 1, wherein the multi-finger end effector includes: multiple tactile sensors configured to interact with the multiple target contact points on the object to sense the tactile signals; and multiple tactile actuators configured to perform the selected action sequences to facilitate the multiple tactile sensors to interact with the multiple target contact points [See Fig. 1].
Additionally, Claim 8 merely recites the intended use of the claimed invention. The recitation must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art is capable of performing the intended use, then it meets the claim. In this case, a robot arm with an end effector that has tactile sensors and performs actions, is covered under Adelson.
Claim(s) 4, 5, 6, 11, 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Adelson (US 20240025039) in view of Chu (US 20210379758) and Zeng (US 20230130977), further in view of Tsukamoto (US 20240131724).
Claim 4, Adelson discloses the system according to claim 1, but does not specifically teach further comprising an image capturing device configured for capturing an image of the object; and wherein the information processing unit further includes an object classifier configured for identifying the classification and a geometry of the object on basis of the captured image and determining the one or more properties to be estimated; and the data management unit is further configured to store the identified geometry and classification of the object and the determined one or more properties to be estimated.
However, Tsukamoto discloses an end effector includes a first sensor and a tactile sensor unit and a force acceptance portion provided for each finger portion, capable of detecting a pressure distribution in a contact region coming into contact with a workpiece (material), and a second sensor capable of detecting position information of the contact region [evaluating properties of a material; see p0003 – p0007].
Further disclosing, robot system includes a robot control apparatus 1, an articulated robot 10, a camera 13, and a jig apparatus 14. The articulated robot 10 may be used for work such as assembly work, fitting work, transport work, palletizing work, or unpacking work. The camera 13 photographs the workpiece and outputs a captured image to the control unit 3. The camera 13 may be provided in the robot hand 12 or may be provided in a place at which a workpiece can be photographed, other than the robot hand 12. Also disclosing in step S11, see Fig 16, when the material 101 is conveyed by the conveying apparatus such as the belt conveyor and stopped at the prescribed position, the control unit 3 controls the camera 13 to photograph the material 101 using the camera 13, and acquires position information of the material 101 from an image obtained by photographing the material 101 [see Figs 1, 16 and p0069, p0098, p0187].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include comprising an image capturing device configured for capturing an image of the object; and wherein the information processing unit further includes an object classifier configured for identifying the classification and a geometry of the object on basis of the captured image and determining the one or more properties to be estimated; and the data management unit is further configured to store the identified geometry and classification of the object and the determined one or more properties to be estimated, as suggested and taught by Tsukamoto, with a reasonable expectation of success, for the purpose of providing the robot with visual feedback on the position, orientation and movement of the end effector and the objects it interacts with, which is crucial for precise positioning and manipulation.
Claim 13 is similarly rejected as Claim 4, see above.
Claim 5, Adelson discloses the system according to claim 1, but is silent to wherein the action selector is further configured for: selecting one or more initial action sequences to be performed by the multi-finger end effector on basis of the prior information of the object and the one or more properties to be estimated;
retrieving the prior information of the object and the one or more properties to be estimated from the data management unit;
evaluating uncertainty levels of the one or more properties of the object estimated by
the property estimator;
comparing, by the action selector, the uncertainty levels against a threshold value; and
selecting one or more supplementary action sequences to be performed by the multi-
finger end effector for obtaining supplementary tactile signals from the multiple target contact points to minimize the uncertainty levels.
However, Chu discloses a method includes: obtaining, via a set of sensors, a representation of an environment; identifying a plurality of markers in the representation of the environment, each marker from the plurality of markers associated with a physical object from a plurality of physical objects located in the environment; an end effector with tactile sensors 357 disposed on the end of the end effectors which can measure the object in an environment. Further disclosing, robotic device 400 can engage in adaptive sensing where sensing can be performed based on stored knowledge and/or a user input. For example, robotic device 400 can identify an area in the environment to scan for an object based on prior information that is has on the object [see p0084, p0101].
Chu discloses robotic device 400 can engage in adaptive sensing where sensing can be performed based on stored knowledge and/or a user input. For example, robotic device 400 can identify an area in the environment to scan for an object based on prior information that is has on the object [see p0084, p0101].
Chu further discloses, a data management unit configured for storing a pool of action sequences available to be selected by the action selector, the prior information of the object, the one or more properties to be estimated, the one or more action sequence performed by the multi-finger end effector and the one or more properties of the object estimated by the property estimator; wherein the tactile signals sensed from each contact point include signals indicative of a normal component and one or more tangential components of a contact force applied by the tactile sensor on the contact point [see p0062 – p0063, p0070 for force applied by tactile sensors; p0078 – algorithms for machine learning, p0084, Fig 12 and p0144].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include retrieving the prior information of the object and the one or more properties to be estimated from the data management unit, as suggested and taught by Chu, with a reasonable expectation of success, for the purpose of providing robotic systems that can perceive and adapt to dynamic and unstructured environments, and can perform tasks within those environments, without relying on pre-programmed manipulation skills.
Neither Adelson nor Chu specifically disclose evaluating uncertainty levels of the one or more properties of the object estimated by the property estimator;
comparing, by the action selector, the uncertainty levels against a threshold value; and
selecting one or more supplementary action sequences to be performed by the multi-
finger end effector for obtaining supplementary tactile signals from the multiple target contact points to minimize the uncertainty levels.
However, Tsukamoto discloses an end effector includes a first sensor and a tactile sensor unit and a force acceptance portion provided for each finger portion, capable of detecting a pressure distribution in a contact region coming into contact with a workpiece (material), and a second sensor capable of detecting position information of the contact region [evaluating properties of a material; see p0003 – p0007].
Further disclosing, comparing, by the action selector, the uncertainty levels against a threshold value, the sensor ICs 4A and 4B may pre-calibrate the output values of the respective detection units, convert the output values into pressure values (kPa), and output the pressure values to the control unit, and the control unit 3 may compare a maximum output value (maximum pressure) among the output values of the respective detection units with the threshold value. Also see Figs 4A – 4B, with a first threshold value is a threshold value for determining whether or not the contact region 122AS of the finger portion 120A and the contact region 122BS of the finger portion 120B are in contact with the workpiece (material). The second threshold value is a threshold value for determining whether or not the prescribed work is progressing normally. For example, in the case of work for bending a workpiece, the second threshold value is a threshold value for determining whether or not a range of load applied to the contact regions 122AS and 122BS in normal bending work is exceeded. The third threshold value is a threshold value for determining whether or not the workpiece is bent [see Figs 4A – 4B, p0090 – p0096].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson as modified to include evaluating uncertainty levels of the one or more properties of the object estimated by the property estimator; comparing, by the action selector, the uncertainty levels against a threshold value; and selecting one or more supplementary action sequences to be performed by the multi-finger end effector for obtaining supplementary tactile signals from the multiple target contact points to minimize the uncertainty levels, as suggested and taught by Tsukamoto with a reasonable expectation of success, for the purpose of providing a control system that is capable of measuring a workpiece (material) for its deformation point without shearing or forcing into rupture, thus just determining the proper output to work the material into a value that is measurable for the certain action.
Claim 12 is similarly rejected as Claim 5, see above.
Claim 6, as best understood, see 112 above, Adelson discloses the system according to claim 5, wherein the uncertainty levels are variances of the one or more properties of the object estimated by the property estimator [see p0004, p0031 – p0033; certain types of robot manipulation tasks may be extremely sensitive to the physical properties of the manipulated objects. For example, some manipulation of the object may use gravity or arm accelerations, increasing the importance of total mass, location center of mass, moment of inertia and/or coefficient of friction. More generally, control of motion of the combination of the robot and the object being manipulated may depend on the physical properties of the object; the controller makes use of the model 126 to act on a control input 124 to cause a desired motion of the object by determining control inputs to the physical robot 140 that depend both on the control input and the physical properties of the object represented in the model 126].
Claim(s) 9, 10 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Adelson (US 20240025039) in view of Chu (US 20210379758) and Zeng (US 20230130977), further in view of Hayashi (US 20240100698).
Claim 9, as best understood, see 112 above, Adelson discloses the system according to claim 8, but not specifically wherein the multi-finger end effector further includes multiple posture sensors configured for sensing postures of the multiple tactile sensors respectively; and the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector and the postures of the multiple tactile sensors.
However, Hayashi discloses the relative position and posture of the end effector and the gripping object are uncertain, and may change during operation. Moreover, the value of the target position and posture of the object in the robot coordinate system is uncertain. In particular, in a case in which a position and a posture of an object to be gripped or an object to be assembled are not determined with high accuracy by a jig, these uncertainties increase.
The integration of posture sensors with end-effectors enhances the functionality and safety of robotic systems, allowing them to perform complex tasks with improved compliance and adaptability [see Summary]. Further teaching, the robot control device including: a target state setting unit that sets an intermediate target state or the completion state as a target state of current movement, the intermediate target state being a target state in a middle of movement of the operation object until reaching the completion state; an observation unit that acquires an observation result by a sensor regarding a position and a posture of the operation object and presence or absence of contact between the operation object and the object of interest [see Figs 2, 6 and p0008 – p0009 p0023, p0028 and p0048].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson as modified to include wherein the multi-finger end effector further includes multiple posture sensors configured for sensing postures of the multiple tactile sensors respectively; and the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector and the postures of the multiple tactile sensors, as suggested and taught by Hayashi, with a reasonable expectation of success, for the purpose of providing the relative position and posture of the end effector and the gripping object are certain, and does not change during operation. Further by using posture sensors, the robot controller will provide the device to accurately operate an operation object.
Claim 14 is similarly rejected as Claim 9, see above.
Claim 10, as best understood, see 112 above, Adelson discloses system according to claim 9, but does not specifically teach further comprising one or more thermal sensors for collecting thermal information of the object; and wherein the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector, the postures of the multiple tactile sensors and the collected thermal information.
However, Chu discloses, See Fig 4, sensors include position encoders, torque and/or force sensors, touch and/or tactile sensors, image capture devices such as cameras, temperature sensors, pressure sensors, light sensors, etc. Skill model(s) 334 are models that have been generated for performing different actions, and represent skills that have been learned by a robotic device. In some embodiments, each model 334 is associated with a set of markers that are tied to different physical objects in an environment. Marker information 335 can indicate which markers are associated with a particular model 334. Each model 334 can also be associated with sensory information 336 that is collected, e.g., via one or more sensors of a robotic device, during kinesthetic teaching and/or other demonstrations of a skill [see Fig 4, p0062, p0070, p0082 – p0084].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson to include comprising one or more thermal sensors for collecting thermal information of the object; and wherein the property estimator is further configured to estimate the one or more properties of the object on basis of the tactile signals sensed by the multi-finger end effector, the action sequence performed by the multi-finger end effector, as suggested and taught by Chu, with a reasonable expectation of success, for the purpose of providing sensors that capture information about the environment and/or objects in the environment around robotic device. The sensory information associated with the manipulating element, where the motion of the manipulating element is associated with a physical interaction between the manipulating element and the set of physical objects, ensuring safety and given certainty in a dynamic environment.
Neither Adelson nor Chu disclose the action sequence performed by the multi-finger end effector, the postures of the multiple tactile sensors.
However, Hayashi discloses the relative position and posture of the end effector and the gripping object are uncertain, and may change during operation. Moreover, the value of the target position and posture of the object in the robot coordinate system is uncertain. In particular, in a case in which a position and a posture of an object to be gripped or an object to be assembled are not determined with high accuracy by a jig, these uncertainties increase.
The integration of posture sensors with end-effectors enhances the functionality and safety of robotic systems, allowing them to perform complex tasks with improved compliance and adaptability [see Summary]. Further teaching, the robot control device including: a target state setting unit that sets an intermediate target state or the completion state as a target state of current movement, the intermediate target state being a target state in a middle of movement of the operation object until reaching the completion state; an observation unit that acquires an observation result by a sensor regarding a position and a posture of the operation object and presence or absence of contact between the operation object and the object of interest [see Figs 2, 6 and p0008 – p0009 p0023, p0028 and p0048].
It would have been obvious before the effective date of the claimed invention to one of ordinary skill in the art to modify the device in Adelson as modified to include the action sequence performed by the multi-finger end effector, the postures of the multiple tactile sensors, as suggested and taught by Hayashi, with a reasonable expectation of success, for the purpose of providing the relative position and posture of the end effector and the gripping object are certain, and does not change during operation. Further by using posture sensors, the robot controller will provide the device to accurately operate an operation object.
Response to Arguments
Applicant’s arguments with respect to all claim(s) have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Renee LaRose/Examiner, Art Unit 3657
/ABBY LIN/Supervisory Patent Examiner, Art Unit 3657
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