DETAILED ACTION
Status of Claims
Claims 1-2, 4-5, and 7-16 are currently pending and have been examined in this application. This Non-final communication is the first action on the merits.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 11/05/2025. 1/30/2026 and 4/21/2026 were filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments and Amendments
Applicant’s arguments, filed on 12/17/2025, with respect to the rejection of Claims 1-2, 4-5, and 7-16 under 35 USC 103 have been fully considered but they are moot in view of the new grounds of rejection provided below, which was necessitated based on Applicant’s amendments to the claims, which changed the scope of the claims. Examiner notes wherein Applicant’s arguments are directed towards the newly amended claim limitation(s), which are addressed by the newly found prior art, as indicated below.
The Examiner further notes wherein that the applicant has used alternative claim language (“or”) with respect to the choice of cost function parameters, in claims 1, 4, and 8. Therefore the examiner has determined that the art applied in the 103 rejection below reads on the claims by addressing a single cost function parameter from among the parameter choices cited in the claim limitations. (see 103 rejections for claims 1, 4, and 8 below)
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.
Claims 1, 2, 4, 5, 7 and 9-12 are rejected under 35 U.S.C. 103 as being unpatentable over Eliasson (US 20110106308 A1) as modified by Seno (US 20190275675 A1)
Claim 1:
Eliasson teaches the following limitations:
A method for controlling displacement from an initial pose to a target pose of a robot that is displaceable in a plurality of coordinates, comprising: (Eliasson – [0034] … This method calculates the movements of the axes of the robot for different tool orientations based on a kinematic model of the robot. Outputs from the optimization are the Cartesian tool position in the target point and the optimized tool orientation in the target point. The optimization uses the kinematic model to find the axes configurations for each target point with tolerances that minimizes the movements for the predefined axes between two or more target points)
providing a movement command, which specifies at least the target pose and a nominal path to be followed from the initial pose to the target pose; (Eliasson - [0027] The computing unit 24 is further configured to determine movements of the robot between the target points on the programmed path for a plurality of different tool orientations within the received tool intervals, and to select new tool orientations for the target points based on the determined movements of the robot with regard to minimizing cycle time. Preferably, the computing unit includes an optimization algorithm which is configured to search for optimal orientations of the tool within the tolerance interval at the target points with regard to minimize the cycle time. …) associating to the movement command an allowed deviation from the nominal path;
(Eliasson – [0008] … The tolerance interval is, for example, chosen by the robot programmer and may vary from an arbitrary orientation of the tool to only allow a small tilt of the tool. The invention makes it possible to have the same tolerance interval for all target points on the movement path, or to have different tolerance intervals for different target points on the movement path. …) identifying a real path, wherein the real path deviates from the nominal path by no more than the allowed deviation; (Eliasson – [0009] The optimization can be performed for some of the programmed target points, or for all target points on the path. For each target point to be optimized, the movements of the robot is determined for a plurality of different tool orientations within the give tolerance interval, and the optimal orientation for the tool in the target point is selected among the different tool orientations with regard to minimizing the cycle time. When optimal orientations of the tool have been determined for the target points, a robot program is generated based on the programmed tool positions and the determined optimal tool orientations. If the tool orientation is not optimized for some of the targets, the robot program is generated based on the programmed tool orientations.)
controlling the robot to move along the real path (Eliasson – [0028] … When the computing unit 24 has finished the optimization, the program generator 28 generates a new robot program based on the new optimized orientations at the target points. The optimized robot program is transferred to a robot controller 32, which downloads the optimized robot program. Then, the robot system is ready for running the optimized robot program. …)
Eliasson does not explicitly teach the following limitations, however Seno teaches:
wherein the real path is determined by minimizing a predetermined cost function,
(Seno - [0058] The path search unit 125 uses a configuration space whose joint angle of each joint axis classified as the path search axis group (hereinafter simply referred to as the path search axis) is the axis, and searches a path where cost corresponding to the selected evaluation function is the smallest.)
wherein the predetermined cost function is configured to increase along with one or more parameters comprising execution time of the movement command and closeness of a joint speed of the robot to a resonant speed; and
(Seno - [0037] … Furthermore, for example, when the third evaluation function “minimization of operating time cost” is selected, the trajectory is planned such that the operating time of the robot is shortest. …)
by weighting one or more parameters of the predetermined cost function, wherein the one or more parameters are weighted based on user input.
(Seno - [0038] The user may simultaneously select a plurality of evaluation functions. Thus, in this case, the trajectory that minimizes the weighted sum of the selected plural evaluation functions is planned. Further, in this case, the user may be able to set the weighting coefficients of the plurality of evaluation functions.)
Examiner’s Note:
Wherein it is noted that the “optimized robot program” corresponds to the “real path” of the instant application.
Wherein it is noted that the “tolerance interval” corresponds to the “safe deviation” of the instant application.
The Examiner further notes wherein that the applicant has used alternative claim language (“or”) with respect to the choice of cost function parameters, in claims 1, 4, and 8. Therefore the examiner has determined that the art applied reads on the claim by addressing a single cost function parameter from among the parameter choices cited in the claim limitations.
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of allowing the user to set the weighted evaluation cost function prior to the start of robot movement, as taught in Seno. Allowing the user to set the evaluation function prior to the start of robot movement, enables the user to adjust the weighted cost function to better match the current conditions under which the robot is operating.
Claim 2:
Eliasson teaches the following limitations:
The method of claim 1, wherein the real path is determined, and control information associated to the real path is stored in a memory before the robot has reached the initial pose, and wherein the stored information is retrieved from the memory to carry out control the robot to move along the real path. (Eliasson – [0037] The found optimized tool orientation is stored as the tool orientation for the target point, block 50. The steps 44-52 of the method are repeated for each target point on the path. When all points on the target have been looped through a new robot program is generated based on the Cartesian positions of the target points and the new optimized tool orientations for the target points for which a tolerance interval has been given, block 54. For the target points which have not received a tolerance interval the originally programmed tool orientations are kept and the new robot program is generated based on the originally programmed tool orientations for those target points.)
Claim 4:
Eliasson teaches the following limitations:
A method for controlling displacement of a robot in a plurality of coordinates from an initial pose to a target pose, comprising: (Eliasson – [0034] … This method calculates the movements of the axes of the robot for different tool orientations based on a kinematic model of the robot. Outputs from the optimization are the Cartesian tool position in the target point and the optimized tool orientation in the target point. The optimization uses the kinematic model to find the axes configurations for each target point with tolerances that minimizes the movements for the predefined axes between two or more target points) providing a movement command, the movement command specifying at least a nominal target pose; (Eliasson - [0027] The computing unit 24 is further configured to determine movements of the robot between the target points on the programmed path for a plurality of different tool orientations within the received tool intervals, and to select new tool orientations for the target points based on the determined movements of the robot with regard to minimizing cycle time. Preferably, the computing unit includes an optimization algorithm which is configured to search for optimal orientations of the tool within the tolerance interval at the target points with regard to minimize the cycle time. …) associating to the movement command an allowed deviation from the nominal target pose; (Eliasson – [0008] … The tolerance interval is, for example, chosen by the robot programmer and may vary from an arbitrary orientation of the tool to only allow a small tilt of the tool. The invention makes it possible to have the same tolerance interval for all target points on the movement path, or to have different tolerance intervals for different target points on the movement path. …) identifying a real target pose that deviates from the nominal target pose by no more than the allowed deviation, (Eliasson – [0009] The optimization can be performed for some of the programmed target points, or for all target points on the path. For each target point to be optimized, the movements of the robot is determined for a plurality of different tool orientations within the give tolerance interval, and the optimal orientation for the tool in the target point is selected among the different tool orientations with regard to minimizing the cycle time. When optimal orientations of the tool have been determined for the target points, a robot program is generated based on the programmed tool positions and the determined optimal tool orientations. If the tool orientation is not optimized for some of the targets, the robot program is generated based on the programmed tool orientations.)
controlling the robot to move to the real target pose (Eliasson – [0028] … When the computing unit 24 has finished the optimization, the program generator 28 generates a new robot program based on the new optimized orientations at the target points. The optimized robot program is transferred to a robot controller 32, which downloads the optimized robot program. Then, the robot system is ready for running the optimized robot program. …)
Eliasson does not explicitly teach the following limitations, however Seno teaches:
wherein the real path is determined by minimizing a predetermined cost function,
(Seno - [0058] The path search unit 125 uses a configuration space whose joint angle of each joint axis classified as the path search axis group (hereinafter simply referred to as the path search axis) is the axis, and searches a path where cost corresponding to the selected evaluation function is the smallest.)
wherein the predetermined cost function is configured to increase along with one or more parameters comprising execution time of the movement command and closeness of a joint speed of the robot to a resonant speed; and
(Seno - [0037] … Furthermore, for example, when the third evaluation function “minimization of operating time cost” is selected, the trajectory is planned such that the operating time of the robot is shortest. …)
by weighting one or more parameters of the predetermined cost function, wherein the one or more parameters are weighted based on user input.
(Seno - [0038] The user may simultaneously select a plurality of evaluation functions. Thus, in this case, the trajectory that minimizes the weighted sum of the selected plural evaluation functions is planned. Further, in this case, the user may be able to set the weighting coefficients of the plurality of evaluation functions.)
Examiner’s Note:
The Examiner further notes wherein that the applicant has used alternative claim language (“or”) with respect to the choice of cost function parameters, in claims 1, 4, and 8. Therefore the examiner has determined that the art applied reads on the claim by addressing a single cost function parameter from among the parameter choices cited in the claim limitations.
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of allowing the user to set the weighted evaluation cost function prior to the start of robot movement, as taught in Seno. Allowing the user to set the evaluation function prior to the start of robot movement, enables the user to adjust the weighted cost function to better match the current conditions under which the robot is operating.
Claim 5:
Eliasson teaches the following limitations:
The method of claim 4, wherein the real target pose is determined, wherein control information associated to the real target pose is stored in a memory before the robot has reached the initial pose, and wherein the control information is retrieved from the memory and used to control the robot to move to the real target pose.
(Eliasson – [0037] The found optimized tool orientation is stored as the tool orientation for the target point, block 50. The steps 44-52 of the method are repeated for each target point on the path. When all points on the target have been looped through a new robot program is generated based on the Cartesian positions of the target points and the new optimized tool orientations for the target points for which a tolerance interval has been given, block 54. For the target points which have not received a tolerance interval the originally programmed tool orientations are kept and the new robot program is generated based on the originally programmed tool orientations for those target points.)
Claim 7:
Eliasson does not explicitly teach the following limitations, however Seno teaches:
The method of claim 4, wherein the movement command or a setting command preceding the movement command specifies the predetermined cost function.
(Seno – [0071] … the evaluation function information 104 input from the user via the input/output unit 110 may be acquired.)
Examiner’s Note:
Wherein it is noted that the “evaluation function” corresponds to the “cost function” of the instant application.
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of allowing the user to set the weighted evaluation cost function prior to the start of robot movement, as taught in Seno. Allowing the user to set the evaluation function prior to the start of robot movement, enables the user to adjust the weighted cost function to better match the current conditions under which the robot is operating.
Claim 9:
Eliasson does not explicitly teach the following limitations, however Seno teaches:
The method of claim 4, wherein a value derived from at least one cost function is displayed to a user.
(Seno - [0036] FIG. 3 illustrates an example of the evaluation function information 104. In FIG. 3, five types of evaluation functions are prepared in advance, and a state in which the first evaluation function “minimization of the change amount cost of the joint” is selected by the user is shown. ; [see also fig. 3] )
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of displaying cost function information for the user, as taught in Seno. Displaying cost function information for the user, allows the user to set the evaluation function prior to the start of robot movement and enables the user to adjust the cost function to better match the current conditions under which the robot is operating with the assistance of a visual display.
Claim 10:
Eliasson does not explicitly teach the following limitations, however Seno teaches:
The method of claim 4, wherein the predetermined cost function is defined by a user.
(Seno – [0038] … Further, in this case, the user may be able to set the weighting coefficients of the plurality of evaluation functions. Further, the evaluation function is not limited to the example shown in FIG. 3, and other evaluation functions may be adopted.)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of allowing the user to set the weighted evaluation cost function prior to the start of robot movement, as taught in Seno. Allowing the user to set the evaluation function prior to the start of robot movement, enables the user to adjust the weighted cost function to better match the current conditions under which the robot is operating.
Claim 11:
Eliasson does not explicitly teach the following limitations, however Seno teaches:
The method of claim 4, wherein the predetermined cost function depends on a plurality of parameters, wherein at least one of the plurality of parameters varies with time.
(Seno – [0037] … Furthermore, for example, when the third evaluation function “minimization of operating time cost” is selected, the trajectory is planned such that the operating time of the robot is shortest. For example, when the fourth evaluation function “minimization of acceleration cost+operating cost applied to the arm tip” is selected, the trajectory is planned to adopt an optimum value by adding the acceleration cost and the operating cost applied to the robot arm tip. …)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include time based parameter adjustment to cost functions, as taught in Seno. Having the ability to minimize operating time as a cost function parameter increases the robots efficiency as it moves along its trajectory.
Claim 12:
Eliasson does not explicitly teach the following limitations, however Seno teaches:
The method of claim 4, wherein the predetermined cost function is one from a plurality of cost functions associated to different sets of values of a plurality of parameters, and wherein the one function is selected based on a current set of values of said parameters.
(Seno - [0038] The user may simultaneously select a plurality of evaluation functions. Thus, in this case, the trajectory that minimizes the weighted sum of the selected plural evaluation functions is planned. Further, in this case, the user may be able to set the weighting coefficients of the plurality of evaluation functions. Further, the evaluation function is not limited to the example shown in FIG. 3, and other evaluation functions may be adopted.)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson to include a method of allowing the user to select an evaluation function from a plurality of evaluation functions, as taught in Seno. Allowing the user to select the evaluation function, enables the user to adjust the cost function to better match the current conditions under which the robot is operating
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Eliasson (US 20110106308 A1) as modified by Seno (US 20190275675 A1) in view of Butterfoss (US 20190366543 A1)
Claim 8:
Eliasson does not explicitly teach the following limitations, however Butterfoss teaches:
The method of claim 4, wherein the predetermined cost function is configured to increase along with one or more of the following parameters: total energy required to execute the movement command, peak power required to execute the movement command, and load imposed on each one of actuators of the robot when executing the command.
(Butterfoss – [0067] … Other examples of task execution criteria involve applying a cost function to identify a maximum amount of joint motion for executing the task, an amount of energy to be used in executing the task, among others.)
Examiner’s Note:
The Examiner further notes wherein that the applicant has used alternative claim language (“or”) with respect to the choice of cost function parameters, in claims 1, 4, and 8. Therefore the examiner has determined that the art applied reads on the claim by addressing a single cost function parameter from among the parameter choices cited in the claim limitations.
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson and Seno to include a cost function that evaluates the energy cost of operating specific robot joints as taught in Butterfoss. Having the ability to assign a cost function to the energy consumption of specific robot joints allows the system to increase the energy efficiency of the robot joint movement as it performs a task.
Claim(s) 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Eliasson (US 20110106308 A1) as modified by Seno (US 20190275675 A1) in view of Kojima (US 20220032459 A1)
Claim 13:
Eliasson does not explicitly teach the following limitations, however Kojima teaches:
The method of claim 1, further comprising monitoring a vicinity of the robot for a change of position of an object, (Kojima - [0064] Based on the acquired environment information, the path generation section 12 identifies the position and shape of the obstacle (hereafter referred to as “obstacle information”) after obstruction occurred. More specifically, the path generation section 12 identifies information regarding obstacles present at the periphery of the robot 30 after obstruction occurred …) wherein identifying a real target pose that deviates from the nominal target pose by no more than the allowed deviation is repeated when a change has been observed. (Kojima - [0068] The path generation section 12 generates a path of the robot 30 from the current pose to a safe pose based on the identified obstacle information, on the acquired robot specification information and safe pose information, and on the notified current pose information. …)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson and Seno to include a method of acquiring information about the robot environment and applying the development of a safe pose, as taught in Kojima. Having the ability to acquire information on the robot environment and control the conditions and parameters under which a robot pose is developed allows for a safer robot pose implementation and reduces the likelihood of damage to equipment or injury to nearby operators.
Claim 14:
Eliasson does not explicitly teach the following limitations, however Kojima teaches:
The method of claim 1, further comprising monitoring a vicinity of the robot for a presence of objects in the vicinity, (Kojima - [0064] Based on the acquired environment information, the path generation section 12 identifies the position and shape of the obstacle (hereafter referred to as “obstacle information”) after obstruction occurred. More specifically, the path generation section 12 identifies information regarding obstacles present at the periphery of the robot 30 after obstruction occurred …) deciding a safe deviation based on said monitoring, and setting a safe deviation as the allowed deviation in the movement command based on the safe deviation. (Kojima - [0068] The path generation section 12 generates a path of the robot 30 from the current pose to a safe pose based on the identified obstacle information, on the acquired robot specification information and safe pose information, and on the notified current pose information. …)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson and Seno to include a method of acquiring information about the robot environment and applying the development of a safe pose, as taught in Kojima. Having the ability to acquire information on the robot environment and control the conditions and parameters under which a robot pose is developed allows for a safer robot pose implementation and reduces the likelihood of damage to equipment or injury to nearby operators.
Claim 15:
Eliasson does not explicitly teach the following limitations, however Kojima teaches:
The method of claim 4, further comprising monitoring a vicinity of the robot for a change of position of an object, (Kojima - [0064] Based on the acquired environment information, the path generation section 12 identifies the position and shape of the obstacle (hereafter referred to as “obstacle information”) after obstruction occurred. More specifically, the path generation section 12 identifies information regarding obstacles present at the periphery of the robot 30 after obstruction occurred …) wherein identifying a real target pose that deviates from the nominal target pose by no more than the allowed deviation is repeated when a change has been observed.
(Kojima - [0068] The path generation section 12 generates a path of the robot 30 from the current pose to a safe pose based on the identified obstacle information, on the acquired robot specification information and safe pose information, and on the notified current pose information. …)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson and Seno to include a method of acquiring information about the robot environment and applying the development of a safe pose, as taught in Kojima. Having the ability to acquire information on the robot environment and control the conditions and parameters under which a robot pose is developed allows for a safer robot pose implementation and reduces the likelihood of damage to equipment or injury to nearby operators.
Claim 16:
Eliasson does not explicitly teach the following limitations, however Kojima teaches:
The method of claim 4, further comprising monitoring a vicinity of the robot for a presence of objects in the vicinity, (Kojima - [0064] Based on the acquired environment information, the path generation section 12 identifies the position and shape of the obstacle (hereafter referred to as “obstacle information”) after obstruction occurred. More specifically, the path generation section 12 identifies information regarding obstacles present at the periphery of the robot 30 after obstruction occurred …) deciding a safe deviation based on said monitoring, and setting a safe deviation as the allowed deviation in the movement command based on the safe deviation. (Kojima - [0068] The path generation section 12 generates a path of the robot 30 from the current pose to a safe pose based on the identified obstacle information, on the acquired robot specification information and safe pose information, and on the notified current pose information. …)
Therefore, prior to the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Eliasson and Seno to include a method of acquiring information about the robot environment and applying the development of a safe pose, as taught in Kojima. Having the ability to acquire information on the robot environment and control the conditions and parameters under which a robot pose is developed allows for a safer robot pose implementation and reduces the likelihood of damage to equipment or injury to nearby operators.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure or directed to the state of the art is listed on the enclosed PTO-892.
The following is a brief description for relevant prior art that was cited but not applied:
Corcodel (US 11548150 B2) describes a robot that utilizes multi-objective optimization and minimizes a cost function to produce a trajectory that penalizes the difference between a target pose of the object and the final pose of the object placed by the robot.
Johnson (US 20200086482 A1) describes a robot that implements a non-linear trajectory optimization using a collision probability and severity distribution as a cost function to directly compute a trajectory of the robot during the portion of the movement plan which minimizes collision costs.
Schmitt (US 20210046648 A1) describes a method for determining an optimized sequence of movements of a robot device for moving a first object in such a way that the first object is brought into a target position independently of an uncertainty of a position of the first object in relation to a second object and/or independently of an uncertainty of a position of the robot device is provided. The method includes: simulating movement portions of the robot device taking account of the uncertainty of the position of the first object and/or the uncertainty of the position of the robot device; and further employs cost functions to control movement sequences.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALAN LINDSAY OSTROW whose telephone number is (703)756-1854. The examiner can normally be reached M-F 8 - 5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Adam Mott can be reached on (571) 270 5376. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALAN LINDSAY OSTROW/ Examiner, Art Unit 3657
/ADAM R MOTT/Supervisory Patent Examiner, Art Unit 3657
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