DETAILED ACTION
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 .
Status of Claims
This is the first office action on the merits, claims 1-25 are currently pending and addressed below.
Information Disclosure Statement
The Information Disclosure Statement filed on 01/12/2024 has been considered. An initialed copy of the IDS is enclosed herewith.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-18, and 20-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claim 1 is directed toward non-statutory subject matter, as shown below:
STEP 1: Does claim 1 fall within one of the statutory categories? Yes. The claim is directed toward a machine which falls within one of the statutory categories.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claim is directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 6 recites:
A mobile robot comprising: a main body;
a travel driving unit provided in the main body and configured to move the main body;
a data unit in which a map of cleaning areas is stored;
an obstacle detection unit configured to detect an obstacle in front of the main body and to input an obstacle detection signal;
an impact detection sensor disposed in the main body and configured to detect impact between the main body and an external object and to generate an impact detection signal;
and a control unit configured to determine an obstacle in response to an obstacle detection signal input from the obstacle detection unit and to generate the map including information on an area where the main body is capable of traveling among the cleaning areas on the basis of information on the obstacle,
wherein the control unit comprises: an obstacle determination unit configured to determine whether an external object colliding with the main body is an obstacle on the basis of the obstacle detection signal when the impact detection signal is input;
an area calculation unit configured to determine a virtual wall registerable area including a plurality of cells on the basis of a position on the map at which the impact detection signal is input if the obstacle determination unit determines that the external object colliding with the main body is not an obstacle; and
a virtual wall registration unit configured to register one of the plurality of cells within the virtual wall registerable area as a virtual wall in the map according to registration priority.
The highlighted portion of claim 1 above is a mental process that can be practicably performed in the human mind and, therefore, an abstract idea. It merely consists of determining areas an obstacle is, then registering it as a path that should be avoided. This is equivalent to a human controlling the robot, the user bumps the robot into a glass door. The user eyes (signal) didn’t see the glass door, but still hit the glass window. The user brain then mentally resolves this issue by mentally knowing there is obstacle (window) at this specific position within the area to avoid.
The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
As such, a person can mentally avoid obstacle locations. The mere nominal recitation that the transmission is being executed by a computer executing a program does not take the limitation out of the mental process.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claim does not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim 1 recites:
A mobile robot comprising: a main body;
a travel driving unit provided in the main body and configured to move the main body;
a data unit in which a map of cleaning areas is stored;
an obstacle detection unit configured to detect an obstacle in front of the main body and to input an obstacle detection signal;
an impact detection sensor disposed in the main body and configured to detect impact between the main body and an external object and to generate an impact detection signal;
and a control unit configured to determine an obstacle in response to an obstacle detection signal input from the obstacle detection unit and to generate the map including information on an area where the main body is capable of traveling among the cleaning areas on the basis of information on the obstacle,
wherein the control unit comprises: an obstacle determination unit configured to determine whether an external object colliding with the main body is an obstacle on the basis of the obstacle detection signal when the impact detection signal is input;
an area calculation unit configured to determine a virtual wall registerable area including a plurality of cells on the basis of a position on the map at which the impact detection signal is input if the obstacle determination unit determines that the external object colliding with the main body is not an obstacle; and
a virtual wall registration unit configured to register one of the plurality of cells within the virtual wall registerable area as a virtual wall in the map according to registration priority.
The highlighted portion of claim 1 above does not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application.
As noted above, merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea is indicative that the judicial exception has not been integrated into a practical application. Thus, it is clear that the abstract idea is merely implemented on a computer, which is indicative of the abstract idea having not been integrated into a practical application.
The “a data unit..”, “an obstacle detection unit configured to detect…”, and “an impact detection sensor..” steps recited in the claim is recited at a high level of generality (i.e., as a general means of gathering an electronic representation of an area), and amounts to mere data gathering, which is a form of insignificant extra-solution activity.
The “a virtual wall registration unit …” step is also recited at a high level of generality (i.e. as a general action or change being taken based on the results of the mental process) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity.
The one or more data networks, one or more processors, one or more memories storing computer readable instructions, and the computer readable storage medium comprising computer-readable instructions merely describes how to generally, “apply” the otherwise mental judgments in a generic or general purpose computing environment. The one or more data networks, one or more processors, one or more memories storing computer readable instructions, and the computer readable storage medium comprising computer-readable instructions are recited at a high level of generality and merely automate the generating steps.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claim does not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Claim 6 does not recite any specific limitation or combination of limitations that are not well-understood, routine, conventional (WURC) activity in the field. Further, applicant’s specification does not provide any indication that the process steps are performing using anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere performance of an action is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). Further, the Federal Circuit in Trading Techs. Int’l v. IBG LLC, 921 F.3d 1084, 1093 (Fed. Cir. 2019), and Intellectual Ventures I LLC v. Erie Indemnity Co., 850 F.3d 1315, 1331 (Fed. Cir. 2017), for example, indicated that the mere displaying of data, such as the “provid[ing] for …navigational assistance”, is a well understood, routine, and conventional function.
CONCLUSION
Thus, since claim 6 is: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that claim 1 is directed towards non-statutory subject matter.
Independent claims 1 and 25 are likewise rejected as being directed towards ineligible subject matter.
Dependent claims 2-5, 7-18, and 20-24 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. For example, In claim 7, the addition limitations of
“wherein the area calculation unit calculates coordinates of a signal input cell on the map corresponding to the position at which the impact detection signal is input, and determines the signal input cell and at least one neighboring cell adjacent to the signal input cell as the virtual wall registerable area.”, under the broadest reasonable interpretation, covers performance of the limitation in the mind using a similar analysis applied to claim 6 above. The apparatus in claim 7, specifically the limitation above, is a mental process that can be practicably performed in the human mind and, therefore, and abstract idea. It is equivalate to a person mentally knowing obstacles in adjacent locations.
As such, claims 1-18, and 20-25 are rejected under 35 USC 101 as being drawn to an abstract idea without significantly more, and thus are ineligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 25 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 25, line 11 recites “as a virtual wall in a map”. It is unclear if this is the same map previously recited or a different map.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-19, and 25, are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Publication No. 20150205299, to Schnittman et al. (hereinafter Schnittman).
Regarding claim 1, and commensurate claim 25, Schnittman teaches, A mobile robot comprising: a main body; a travel driving unit provided in the main body and configured to move the main body; (See at least paragraph [0043] “An autonomous robot movably supported may execute simultaneous localization and mapping (SLAM) on a controller to navigate and negotiate obstacles. For example, an autonomous cleaning robot may execute a SLAM routine navigate a cleaning area and to clean a surface while traversing that area.”). Further, (See at least paragraph [0044] “Referring to FIGS. 1-3, in some implementations, a robot 100 includes a body 110 supported by a drive system 120 that can maneuver the robot 100 across the floor surface 10 based on a drive command having x, y, and .theta. components, for example, issued by a controller 150. The robot body 110 has a forward portion 112 and a rearward portion 114. The drive system 120 includes right and left driven wheel modules 120a, 120b that may provide odometry to the controller 150. The wheel modules 120a, 120b are substantially opposed along a transverse axis X defined by the body 110 and include respective drive motors 122a, 122b driving respective wheels 124a, 124b.”).
a data unit in which a map of cleaning areas is stored; (See at least paragraph [0057] “the robot 100 may use a navigation system 600 to simultaneously localize and map its surroundings, using sensory inputs from the sensor system 500. Simultaneous localization and mapping (SLAM) is a technique the robot 100 may use to build up a map 620 (e.g., an occupancy map) within an unknown environment or scene 10”). Further, (See at least paragraph [0071] “The SLAM controller 610 may accumulate range data 515 in a data buffer 612 (e.g., non-transitory memory) until it has acquired a predefined amount”). Lastly, Further, (See at least paragraph [0043] “an autonomous cleaning robot may execute a SLAM routine navigate a cleaning area and to clean a surface while traversing that area.”).
an impact detection sensor disposed in the main body and configured to detect impact between the main body and an external object and to generate an impact detection signal; Further, (See at least paragraph [0055] “The bumper 130 may include one or more bump sensors 530 (e.g., contact sensor, switch, or infrared proximity sensor) for sensing contact with a bumped object. In some examples, the bumper 130 includes right and left bump sensors 530a, 530b for sensing a directionality of the bump with respect to the forward drive direction (e.g., a bump vector).”).
and a control unit configured to generate the map including information on the cleaning areas, wherein the control unit is configured to: (See at least paragraph [0064] “the navigation system 600 includes a simultaneous localization and mapping (SLAM) controller 610, executable on a computing processor (e.g., on the robot controller 150), that builds maps 620 (e.g., feature based maps, occupancy maps and/or ground plane maps) using sensor data received from the sensor system”).
determine a virtual wall registerable area including a plurality of cells on the basis of a position on the map at which the impact detection signal is input when the impact detection signal is input; and (See at least paragraph [0066] “FIG. 8A illustrates the robot 100 scanning its environment, a scene 10, to obtain range data 515. In this case, a range scan 517 detects a wall 7 intersecting the floor 5 in the scene 10, demarcating a trackable feature 14. FIG. 8B illustrates an exemplary occupancy grid map 620, which may be a 2D-XY grid 622 having cells 624 along an X direction and a Y direction. Each cell 624 of the occupancy grid map 620 contains a probability of occupancy based on the accumulation of range finder data resulting from the existence of an object 12 falling within that cell 624”). Further, (See at least paragraph [0085] “The method includes synchronizing range data 515 and bumper data 535 with change(s) in the robot pose (i.e., .DELTA.Pose data),”). Still further, (See at least paragraph [0088] “The robot 100 may use the wall-following as a virtual proximity sensor when the robot 100 follows the wall at a fixed distance or senses contact with the wall using the bump sensor(s) 530. Moreover, the SLAM controller 610 may add new particles 640 to the particle model 645 based on the virtual proximity sensor data, allowing the robot to not only re-localize off of the wall, but also add reliable particles 640 to the particle model 645.”).
register one of the plurality of cells within the virtual wall registerable area as a virtual wall in the map according to registration priority. (See at least paragraph [0066] “FIG. 8B illustrates an exemplary occupancy grid map 620, which may be a 2D-XY grid 622 having cells 624 along an X direction and a Y direction. Each cell 624 of the occupancy grid map 620 contains a probability of occupancy based on the accumulation of range finder data resulting from the existence of an object 12 falling within that cell 624. In some examples, each cell 624 has a fixed size, such as 5 cm by 5 cm. The occupancy grid map 620 accumulates range data 515 having x and y coordinates from the range finding sensor(s) 510, 510a-d by receiving range points 515 in cells 624 occupying the corresponding x, y values of the range points 515. For example, a first cell occupying x=0-5 cm and y=0-5 cm receives a point 515 having an x value of 3 cm and a y value of 2 cm. Each cell 624 may have a classification. A cell 624f having a probability of occupancy less than 50%, for example, may be classified as unoccupied or free, whereas a cell 624o having an occupancy greater than or equal to 50%, in this example may be classified as occupied..”).
Regarding claim 2, and commensurate claim 7, Schnittman discloses the claimed features of claim 1 and Schnittman further disclose, wherein an area calculation unit calculates coordinates of a signal input cell on the map corresponding to the position at which the impact detection signal is input and determines the signal input cell and at least one neighboring cell adjacent to the signal input cell as the virtual wall registerable area. (See at least paragraph [0066] “The occupancy grid map 620 accumulates range data 515 having x and y coordinates from the range finding sensor(s) 510, 510a-d by receiving range points 515 in cells 624 occupying the corresponding x, y values of the range points 515”). Further, (See at least paragraph [0099] “The sensor data 205, 515, 525, 535 may include range data 515 (e.g., from one or more infrared range finding sensors) and the synchronized sensor data 205, 515, 525, 535 include range measurement and bearing pairs. The bearings may be determined from the known mount locations of the sensors 510a-d.”). Lastly, (See at least paragraph [0061] “ A dynamics model 230 executable on the controller 150 is configured to compute the center for gravity (CG)”).
Regarding claim 3, Schnittman discloses the claimed features of claim 1 and Schnittman further disclose, wherein the control unit calculates coordinates of a signal input cell on the map corresponding to the position at which the impact detection signal is input and determines the signal input cell and at least one neighboring cell adjacent to the signal input cell as the virtual wall registerable area in consideration of a size of the main body, a shape of the main body, and an installation position of the impact detection sensor. (See at least paragraph [0101] “applying the range sensor model 670 includes only updating particle map cells 624 corresponding to the synchronized sensor data 205, 515, 525, 535.”). Further, (See at least paragraph [0080-0081] “When the SLAM controller 610 is confident that the robot pose P is well-known, it may use the range data 515 of the range finders 510a-d to add occupancy probabilities to the occupancy grid map/model 620. However, if the SLAM controller 610 is not confident in the robot's localization, it may skip the step of modifying/updating the occupancy grid map/model 620. All other parts of the SLAM process may proceed as usual. This technique causes the map 620 to become frozen in the last known-good state and to remain that way until the robot 100 is able to regain a high-quality estimate of its position (pose P), at which time the SLAM controller 610 may resume adding occupancy data to the map 620. In short, this technique helps prevent the system from destroying a perfectly good map 620 due to what would otherwise be a temporary loss of localization. If the map 620 becomes significantly corrupted it may be very difficult, if not impossible, to localize successfully.”).
Regarding claim 4, and commensurate claim 9, Schnittman discloses the claimed features of claim 1 and Schnittman further disclose, wherein the control unit determines a first priority cell from among the plurality of cells within the virtual wall registerable area according to the registration priority and registers the first priority cell as a virtual wall in the map according to attributes of the first priority cell. (See at least paragraph [0066] “ FIG. 8B illustrates an exemplary occupancy grid map 620, which may be a 2D-XY grid 622 having cells 624 along an X direction and a Y direction. Each cell 624 of the occupancy grid map 620 contains a probability of occupancy based on the accumulation of range finder data resulting from the existence of an object 12 falling within that cell 624. In some examples, each cell 624 has a fixed size, such as 5 cm by 5 cm. The occupancy grid map 620 accumulates range data 515 having x and y coordinates from the range finding sensor(s) 510, 510a-d by receiving range points 515 in cells 624 occupying the corresponding x, y values of the range points 515. For example, a first cell occupying x=0-5 cm and y=0-5 cm receives a point 515 having an x value of 3 cm and a y value of 2 cm. Each cell 624 may have a classification. A cell 624f having a probability of occupancy less than 50%, for example, may be classified as unoccupied or free, whereas a cell 624o having an occupancy greater than or equal to 50%, in this example may be classified as occupied.”).
Regarding claim 5, and commensurate claim 10, Schnittman discloses the claimed features of claim 1 and Schnittman further disclose, wherein the control unit determines a first priority cell from among the plurality of cells within the virtual wall registerable area according to the registration priority and registers the first priority cell as a virtual wall if attributes of the first priority cell in the map do not indicate a virtual wall. (See at least paragraph [0101] “The method may further include receiving a measured range 515, receiving the predicted range 515, and computing a probability of occupancy of an object 12 in each cell 622 of the particle map 642 along the ray trace. In some examples, applying the range sensor model 670 includes only updating particle map cells 624 corresponding to the synchronized sensor data 205, 515, 525, 535.”). Further, (See at least paragraph [0080] “When the SLAM controller 610 is confident that the robot pose P is well-known, it may use the range data 515 of the range finders 510a-d to add occupancy probabilities to the occupancy grid map/model 620. However, if the SLAM controller 610 is not confident in the robot's localization, it may skip the step of modifying/updating the occupancy grid map/model 620. All other parts of the SLAM process may proceed as usual.”).
Regarding claim 6, which is commensurate to claim 1, but further adds the limitations, that Schnittman discloses, an obstacle detection unit configured to detect an obstacle in front of the main body and to input an obstacle detection signal; (See at least paragraph [0052] “the sensor system 500 includes one or more range finding sensors 510 disposed on the robot body 110 or bumper 130.”). Further, (See at least paragraph [0072] “If the range finders 510a-d fail to receive a reflection from an object, rather than assuming an object is not present, the SLAM controller 610 may ignore the corresponding range data (in lieu of other subsequently acquired data).”). Further, (See at least paragraph [0052] “The range finders 510a-d can detect a distance to objects 12 in a scene 10 about the robot and in the field of view 512 of the range finders 510a-d.”).
and a control unit configured to determine an obstacle in response to an obstacle detection signal input from the obstacle detection unit and to generate the map including information on an area where the main body is capable of traveling among the cleaning areas on the basis of information on the obstacle, wherein the control unit comprises: (See at least paragraph [0056] “The reasoning software processes the data collected from the sensor system 500 and outputs data for making navigational decisions on where the robot 100 can move without colliding with an obstacle”). Further, (See at least paragraph [0064] “Referring to FIGS. 6 and 7, in some implementations, the navigation system 600 includes a simultaneous localization and mapping (SLAM) controller 610, executable on a computing processor (e.g., on the robot controller 150), that builds maps 620 (e.g., feature based maps, occupancy maps and/or ground plane maps) using sensor data received from the sensor system 500. In some examples, the SLAM controller 610 relies on range data 515 (points) received from the range finders 510a-d, gyroscopic data 525 received from the inertial measurement unit 520, bump data 535 received from the bump sensor(s) 530, 503a-b, and/or odometry 205 received from the drive system 200.”).
an obstacle determination unit configured to determine whether an external object colliding with the main body is an obstacle on the basis of the obstacle detection signal when the impact detection signal is input; (See at least paragraph [0072] “If the range finders 510a-d fail to receive a reflection from an object, rather than assuming an object is not present, the SLAM controller 610 may ignore the corresponding range data”). Further, (See at least paragraph [0088] “The robot 100 may use the wall-following as a virtual proximity sensor when the robot 100 follows the wall at a fixed distance or senses contact with the wall using the bump sensor(s) 530.”). Still further, (See at least paragraph [0102] “computing a third occupancy probability assuming failure to detect of an expected close object 12 ”).
an area calculation unit configured to determine a virtual wall registerable area including a plurality of cells on the basis of a position on the map at which the impact detection signal is input if the obstacle determination unit determines that the external object colliding with the main body is not an obstacle; (See at least paragraph [0066] “FIG. 8B illustrates an exemplary occupancy grid map 620, which may be a 2D-XY grid 622 having cells 624 along an X direction and a Y direction.”). (See at least paragraph [0085] “The method includes synchronizing range data 515 and bumper data 535 with change(s) in the robot pose ”). (See at least paragraph [0100] “The robot motion model 660 models movement of the robot 100 based on odometry 205 and inertial measurements 525. Updating the particle map 642 may include executing a ray trace of the accumulated synchronized sensor data 205, 515, 525, 535 and applying a range sensor model 670 to the accumulated synchronized sensor data 205, 515, 525, 535.”).
Regarding claim 8, Schnittman discloses the claimed features of claim 6 and Schnittman further disclose, the area calculation unit calculates coordinates of a signal input cell on the map corresponding to the position at which the impact detection signal is input, and determines the signal input cell and at least one neighboring cell adjacent to the signal input cell as the virtual wall registerable area in consideration of a size of the main body, a shape of the main body, and an installation position of the impact detection sensor. (See at least paragraph [0070] “To aggregate across time the SLAM controller 610 stores sensor measurements as range and bearing pairs originating from the center of the robot 100, along with a best estimate of the robot's pose P (x, y, and .theta. measurements of the robot's center to an arbitrarily oriented coordinate system established when the particular run began).”). Further, (See at least paragraph [0076] “The SLAM controller 610 receives distance estimates of obstacles 12 at a given height off of the floor 5 as dictated by the mounting position and orientation of the sensor (e.g., range finders 510).”).
Regarding claim 11, Schnittman discloses the claimed features of claim 11 and Schnittman further disclose, wherein the virtual wall registration unit determines a second priority cell from among the plurality of cells within the virtual wall registerable area according to the registration priority if the attributes of the first priority cell indicate a virtual wall, and registers the second priority cell as a virtual wall according to attributes of the second priority cell. (See at least paragraph [0102] “ applying the range sensor model 670 includes computing a range error as an absolute difference between the measured range 515 and the predicted range 515 and computing the occupancy probability within each cell 624 of the particle map 642 along the ray trace based on the range error. For each particle map cell 624 along the ray trace, the method may include computing a first occupancy probability assuming detection of an expected object 12, computing a second occupancy probability assuming detection of an expectedly close object 12, computing a third occupancy probability assuming failure to detect of an expected close object 12 within a threshold distance of the robot 100, and computing a weighted average of the first, second, and third occupancy probabilities.”).
Regarding claim 12, Schnittman discloses the claimed features of claim 6 and Schnittman further disclose, wherein the virtual wall registration unit determines an n-th priority cell from among the plurality of cells within the virtual wall registerable area according to the registration priority, registers the n-th priority cell as a virtual wall according to attributes of the n-th priority cell in the map, determines an (n+1)-th priority cell from among the plurality of cells within the virtual wall registerable area according to the registration priority if the n-th priority cell is not able to be registered as a virtual wall according to the attributes of the n-th priority cell, and registers the (n+1)-th priority cell as a virtual wall according to attributes of the (n+1)-th priority cell in the map. (See at least paragraph [0102] “applying the range sensor model 670 includes computing a range error as an absolute difference between the measured range 515 and the predicted range 515 and computing the occupancy probability within each cell 624 of the particle map 642 along the ray trace based on the range error. For each particle map cell 624 along the ray trace, the method may include computing a first occupancy probability assuming detection of an expected object 12, computing a second occupancy probability assuming detection of an expectedly close object 12, computing a third occupancy probability assuming failure to detect of an expected close object 12 within a threshold distance of the robot 100, and computing a weighted average of the first, second, and third occupancy probabilities.”).
Regarding claim 13, Schnittman discloses the claimed features of claim 6 and Schnittman further disclose, wherein the virtual wall registration unit determines the registration priority in descending order of a probability of not detecting impact in areas depending on a position at which the impact detection sensor is disposed. (See at least paragraph [0011] “computing a third occupancy probability assuming failure to detect of an expected close object within a threshold distance of the robot, and computing a weighted average of the first, second, and third occupancy probabilities.”). Further, (See at least paragraph [0093] “The method further includes determining a third probability of occupancy assuming that a long range measurement results from a failure to detect a close object. This may entail assigning a predetermined value.”).
Regarding claim 14, Schnittman discloses the claimed features of claim 6 and Schnittman further disclose, wherein the impact detection sensor comprises: a first impact detection sensor located on the side of the main body between a front end of the main body and a left end of the main body; and a second impact detection sensor located on the side of the main body between the front end of the main body and a right end of the main body. (See at least paragraph [0055] “The bumper 130 may include one or more bump sensors 530 (e.g., contact sensor, switch, or infrared proximity sensor) for sensing contact with a bumped object. In some examples, the bumper 130 includes right and left bump sensors 530a, 530b for sensing a directionality of the bump with respect to the forward drive direction (e.g., a bump vector).”).
Regarding claim 15, Schnittman discloses the claimed features of claim 14 and Schnittman further disclose, wherein, if impact detection signals are simultaneously input from the first impact detection sensor and the second impact detection sensor, the area calculation unit calculates coordinates of a first signal input cell and a second signal input cell on the map corresponding to positions of the first impact detection sensor and the second impact detection sensor, and determines cells between the first signal input cell and the second signal input cell, the first signal input cell, and the second signal input cell as the virtual wall registerable area. (See at least paragraph [0055] “The bumper 130 may include one or more bump sensors 530 (e.g., contact sensor, switch, or infrared proximity sensor) for sensing contact with a bumped object. In some examples, the bumper 130 includes right and left bump sensors 530a, 530b for sensing a directionality of the bump with respect to the forward drive direction (e.g., a bump vector).”). Further, (See at least paragraph [0095] “The method also includes determining a sixth probability of occupancy for cells between the robot and the measured range to the target object.”).
Regarding claim 16, Schnittman discloses the claimed features of claim 15 and Schnittman further disclose, wherein the virtual wall registration unit sets a higher registration priority to a cell farther from a center between the first impact detection sensor and the second impact detection sensor among the cells between the first signal input cell and the second signal input cell. (See at least paragraph [0092] “This may entail assigning one of three range values (e.g., close, medium, and far) based on a range difference.”). Further, (See at least paragraph [0093] “The assigned range value can be based on how much closer the measured range was to the target object than the predicted range. ”).
Regarding claim 17, Schnittman discloses the claimed features of claim 14 and Schnittman further disclose, wherein, if an impact detection signal is input from one of the first impact detection sensor and the second impact detection sensor, the area calculation unit calculates coordinates of a signal input cell on the map corresponding to a position at which the impact detection signal is input, and determines the signal input cell and at least one neighboring cell adjacent to the signal input cell as the virtual wall registerable area in consideration of the size of the main body, the shape of the main body, and the installation position of the impact detection sensor. (See at least paragraph [0064] “bump data 535 received from the bump sensor(s) 530, 503a-b, and/or odometry 205 received from the drive system 200.”). Further, (See at least paragraph [0055] “sensing a directionality of the bump with respect to the forward drive direction (e.g., a bump vector).”). Further, (See at least paragraph [0100] “The robot motion model 660 models movement of the robot 100 based on odometry 205 and inertial measurements 525. Updating the particle map 642 may include executing a ray trace of the accumulated synchronized sensor data 205, 515, 525, 535 and applying a range sensor model 670 to the accumulated synchronized sensor data 205, 515, 525, 535. Updating the particle weight 646 may be based on a number of measured ranges 515 of the accumulated synchronized sensor data 205, 515, 525, 535 matching predicted ranges 515.”). Further, (See at least paragraph [0102] “applying the range sensor model 670 includes computing a range error as an absolute difference between the measured range 515 and the predicted range 515 and computing the occupancy probability within each cell 624 of the particle map 642 along the ray trace based on the range error”).
Regarding claim 18, Schnittman discloses the claimed features of claim 17 and Schnittman further disclose, wherein the virtual wall registration unit sets a higher registration priority to a cell farther from the center between the first impact detection sensor and the second impact detection sensor among the cells in the virtual wall registerable area. (See at least paragraph [0094] “This may entail assigning one of three range values (e.g., close, medium, and far) based on a magnitude of the measured range.”). Further, (See at least paragraph [0075] “Moreover, the IMU 520 may have a different error, depending on it method of measurement (e.g., gyro). The robot motion model 660 may be a Gaussian error model centered on a travel vector derived from a travel vector derived from odometry and/or the IMU 520, where some portion of the Gaussian curve represents noise.”).
Regarding claim 19, Schnittman discloses the claimed features of claim 6 and Schnittman further disclose, wherein the control unit controls the travel driving unit to travel while avoiding a virtual wall registered in the map. (See at least paragraph [0057] “The navigation system 600 allows the robot 100 to navigate a scene 10 without colliding into obstacles 12 ”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 20-24, is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 20150205299, to Schnittman et al. (hereinafter Schnittman), and further in view of U.S. Patent Publication No. 20180074508, to Kleiner et al (hereinafter Kleiner).
Regarding claim 20, Schnittman disclose the claimed features of claim 6, Schnittman fails to explicitly discloses, however Kleiner further disclose, wherein the virtual wall registration unit registers attribute information including time information or information on the number of times of cleaning at the time of registering a virtual wall in the map. (See at least paragraph [0205] “and cleaning mission performance data 2203. Cleaning mission performance data 2203 may include the duration of the cleaning mission, the start and/or end time, a mission status, the amount of area cleaned during the cleaning mission and/or a dirt detection count.”). Further, (See at least paragraph [0208] “the user device may display summary cleaning mission data 2503 corresponding to the living room including how many times the living room was cleaned, the date of the last cleaning, the total time spent cleaning the living room, and/or a date range corresponding to the displayed data.”).
Schnittman as modified by Kleiner, are analogous art because they are in the same field of endeavor, navigating systems. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Schnittman to incorporate the teachings of Kleiner, as both systems are SLAM mapping systems, and address the same problem of dynamic environment obstacles. Therefore, by incorporating Kleiner mission cycle to Schnittman bump generation walls, the robot is able to remove false obstacles in the area.
Regarding claim 21, Schnittman disclose the claimed features of claim 6, Schnittman fails to explicitly discloses, however Kleiner further disclose, wherein the control unit initializes virtual walls for which a certain period of time has elapsed among virtual walls registered in the map. (See at least paragraph [0196] “FIGS. 16E through 16G illustrate the removal of non-static obstacles detected intermittently or only on one or some of the total missions”). Further, (See at least paragraph [0196] “clutter detection can be significantly improved because, when observing obstacles over time, the location of static obstacles may stay the same whereas the locations of clutter/non-static obstacles may change over time.”). Lastly, (See at least paragraph [0221] “the computed coverage pattern may be modified by re-classifying one or more of the clutter areas 2906 as an open area 2904, resulting in a change in the behavior of the robot 100 in navigation of the same surface after the re-classification.”).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Schnittman to incorporate the teachings of Kleiner for the same motivation reasons in claim 20.
Regarding claim 22, Schnittman disclose the claimed features of claim 6, Schnittman fails to explicitly discloses, however Kleiner further disclose, wherein the control unit initializes virtual walls for which a certain number of times of cleaning has passed among the virtual walls registered in the map. (See at least paragraph [0196] “FIGS. 16E through 16G illustrate the removal of non-static obstacles detected intermittently or only on one or some of the total missions”). Further, (See at least paragraph [0196] “clutter detection can be significantly improved because, when observing obstacles over time, the location of static obstacles may stay the same whereas the locations of clutter/non-static obstacles may change over time.”). Lastly, (See at least paragraph [0221] “the computed coverage pattern may be modified by re-classifying one or more of the clutter areas 2906 as an open area 2904, resulting in a change in the behavior of the robot 100 in navigation of the same surface after the re-classification.”).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Schnittman to incorporate the teachings of Kleiner for the same motivation reasons in claim 20.
Regarding claim 23, Schnittman disclose the claimed features of claim 6, Schnittman fails to explicitly discloses, however Kleiner further disclose, wherein the control unit divides the map into a plurality of cleaning areas and, at the time of starting cleaning, initializes a virtual wall located within at least one cleaning area randomly selected from among the plurality of cleaning areas. (See at least paragraph [0186] “FIG. 8C illustrates a segmentation map 822 that may be displayed to the user on the user device. Similar to the cleaned map 812, the segmentation map 822 illustrates the enclosed space with the boundary data 826. Additionally, the traversable space is segmented into regions 824 that may correspond to different rooms in the enclosed space according to some embodiments. Based on the segmentation map 822, the robot may perform room-by-room cleaning in which the cleaning operation in a given region 824 is completed before the robot begins to perform a cleaning operation in another region 824.”). Further, (See at least paragraph [0138] “Some embodiments provide that extracted regions are then merged into corridors and rooms according to heuristic decision rules. Then for each region, starting locations and directions are calculated for systematic room cleaning. Finally, regions are systematically cleaned by the robot according to the shortest sequence computed by route optimization and/or by a sequence selected by a user.”).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Schnittman to incorporate the teachings of Kleiner for the same motivation reasons in claim 20.
Regarding claim 24, Schnittman disclose the claimed features of claim 6, Schnittman fails to explicitly discloses, however Kleiner further disclose, wherein the control unit divides the map into a plurality of cleaning areas at the start of cleaning, and initializes a virtual wall within a cleaning area determined according to the number of times of cleaning when starting cleaning. (See at least paragraph [0186] “FIG. 8C illustrates a segmentation map 822 that may be displayed to the user on the user device. Similar to the cleaned map 812, the segmentation map 822 illustrates the enclosed space with the boundary data 826. Additionally, the traversable space is segmented into regions 824 that may correspond to different rooms in the enclosed space according to some embodiments. Based on the segmentation map 822, the robot may perform room-by-room cleaning in which the cleaning operation in a given region 824 is completed before the robot begins to perform a cleaning operation in another region 824.”). Further, (See at least paragraph [0138] “Some embodiments provide that extracted regions are then merged into corridors and rooms according to heuristic decision rules. Then for each region, starting locations and directions are calculated for systematic room cleaning. Finally, regions are systematically cleaned by the robot according to the shortest sequence computed by route optimization and/or by a sequence selected by a user.”).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the system of Schnittman to incorporate the teachings of Kleiner for the same motivation reasons in claim 20.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Wesam Almadhrhi whose telephone number is (571) 270-3844. The examiner can normally be reached on 7:30 AM - 5PM Mon-Fri Eastern Alt Fri.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Anne Antonucci can be reached on (313) 446-6519. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WESAM NMN ALMADHRHI/Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666
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