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 .
This is a Non-Final Action on the Merits. Claims 1, 5-10, and 14-15 are currently pending and are addressed below.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on January 14th, 2026 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on February 13th, 2026 has been considered and entered.
Response to Amendments
The amendment filed on January 14th, 2026 has been considered and entered. Accordingly, claims 1 and 10 have been amended. Claims 3-4 and 11-13 have been cancelled.
Response to Arguments
The applicant states (Amend 9-10) that Artes (US 20220074762 A1) (“Artes”) fails to disclose the limitation “based on identifying that the robot has a history of travelling in the second region based on the travelling history information of the robot update the first map data with the second map data”. The examiner respectfully disagrees. Artes teaches that temporarily complied map data of a region is incorporated to the previously complied map data of an area (See at least Artes Paragraph 115 “. Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”) such that a determination of the mobile robot being in a previous area is required for the temporary map to be incorporated with the previous map data.
The applicant states (Amend. 10-11) that Artes (US 20220074762 A1) (“Artes”) fails to disclose the limitation “the at least one processor is further configured to: identify a first location corresponding to a current location of the robot based on the first map data, identify a second location corresponding to the current location of the robot based on the second map data, based on a distance between the first location and the second location, the distance being smaller than a threshold distance, identify that the error does not exist in the second map data, and based on the distance between the first location and the second location, the distance being greater than or equal to the threshold distance, identify that the error exists in the second map data” as recited in amended independent claims 1 and 10. The examiner respectfully disagrees. Artes teaches that a mobile robot can compare its location from a temporary map to that of a previously compiled map and if the locations in each map have sufficient matching, then the temporary map is considered to not have an error an only then is the temporary map integrated with the previously compiled map (See at least Artes Paragraph 115 “. Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”). The teachings of Artes discloses the above limitation since the temporary map would only be integrated to the previously complied map if there was not an error present based on the distance being smaller than a threshold distance, and the temporary map would not be integrated to the previously complied map if the distance is greater than a threshold distance, since this would be considered an error in the temporary map.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is:
“a communication interface … to transmit” in at least claim 9
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
The published specification provides a corresponding structure for the claimed limitation in paragraph 88
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 5, 7-10, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Artes (US 20220074762 A1) (“Artes”) in view of Fu (WO 2018223952 A1) (“Fu”) (Translation Attached).
With respect to claim 1, Artes teaches a robot comprising:
at least one memory storing travelling history information of the robot and a map about a space, the map including first map data corresponding to a first region of the space (See at least Artes Paragraph 135 “n order to compile the updated map 502, the changes to the deployment area in comparison to the point in time at which the already existing map 500 was compiled can be determined. For this, in particular the data regarding the structure of the environment that was recorded during the exploration and saved in a new temporary map and the orientation data contained in the existing map 500 (e.g. detected walls, obstacles and other landmarks) are compared. Alternatively or additionally, at the beginning of the exploration run a copy 501 of the permanently saved map 500 can be generated (in particular in the main memory of the processor 155), wherein the robot 100 determines its position in the copy (e.g. using the base station as a starting point or by means of global self-localization). During the renewed exploration the data in this work copy 501 can be directly updated, in the course of which, in particular, obstacles and/or landmarks no longer present are deleted, new obstacles and/or landmarks are added and recognized obstacles and/or landmarks are confirmed. After completion of the renewed exploration, the thus compiled work copy 501 can be compared to the still existing map 500. Alternatively or additionally, the data intended for deletion or addition can be directly utilized to determine what changes were made. When, for example, a newly identified obstacle is added to the map, the information that this obstacle was newly added can also be recorded (e.g. by marking it with a time stamp).”);
a distance sensor configured to acquire distance data while the robot travels in the space (See at least Artes Paragraph 33 “The human machine interface 200 can provide the user with information regarding the autonomous mobile robot 100, for example, in visual or acoustic form (e.g. loading status of batteries, present work task, map information such as a cleaning map, etc.)”);
and at least one processor operatively connected to the at least one memory and the distance sensor, wherein the at least one processor is configured to: acquire second map data based on the distance data, compare the first map data and the second map data and generate a comparison result (See at least Artes Paragraph 123 “As an alternative, instead of deleting the map data, the problem area may again be explored. For example, the robot may recognize (as described above) that it is locked in in a given area, e.g. due to a door falling shut. In this case the robot would notify the user via the HMI 200 so that door, and with it the robot's path, can be opened, thus liberating the robot. Afterwards the user can tell the robot via the HMI 200 to carry on with the exploration. In such a case it may be useful for the problem area (that is, the room) to be, entirely or partially, explored again. The doorway (of the reopened door), for example, can now be recognized as freely accessible. The renewed exploration of the problem area may start from its edge or even be limited to its edge (e.g. locating and identifying the doorway).” | Paragraph 138 “The robot is capable of recognizing, for example, when floor covering borders have been moved, such as in the example from FIG. 12 involving the carpet C. If the dimensions of the carpet C (i.e. length, width and height) have remained unchanged, this information concerning the floor covering can be carried over from the previously existing map 500 into the updated map 502 and only the position data has to be updated. The carpet C may additionally be associated with a subarea created by the user. The position of this subarea can also be automatically updated to the new position of the carpet C, e.g. based on the floor covering borders”),
and based on the comparison result indicating that an error does not exist in the second map data and based on identifying that the second map data comprises information on a second region of the space, update the first map data of the data with the second map data (See at least Artes Paragraph 139 “Danger zones linked to obstacles or objects can also be updated, for example. Further, a carpet C such as the one shown in FIG. 12 may also have a wide fringe that could become tangled in a rotating brush during cleaning. To avoid this, this side of the carpet can be marked in the original map 500 to be cleaned only with the brushes turned off. This metadata (e.g. saved in the map as an attribute of the subarea) can also be carried over to the new position of the carpet C. This means that metadata that concern the behavior or operation of the service unit 160 can also be automatically adapted to the updated subarea (which, in this example, is defined by the carpet C).”). and
travel the spacing using the map including the second map data (See at least Artes Paragraph 142 “The robot 100 may carry out a renewed exploration run through the deployment area DA and thereby expand the map such that the room R will be entered into the updated map so that it is taken into account and included in the planning of future deployments. When starting the renewed exploration run, the user can let the entire deployment area DA be newly explored and/or select a subarea for the exploration. For example, the user may send the robot 100 to a point before the opened door to room R. The robot would then begin exploring its environment starting at this point and would immediately recognize that the mapping of the deployment area is not yet complete. The robot recognizes that the room R lying behind the door is an accessible surface and will explore the room R in order to correspondingly expand the map. The new orientation data (i.e. the detected walls, obstacles and other landmarks) that concern the room R (including the information regarding the now open doorway) are then entered into the updated map 502. The remaining orientation data can be carried over unchanged into the updated map.”)
wherein the at least one processor is further configured to: based on identifying that the robot has a history of travelling in the second region based on the travelling history information of the robot update the first map data with the second map data (See at least Artes Paragraph 115 “Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”)
wherein the at least one processor is further configured to: identify a first location corresponding to a current location of the robot based on the first map data, identify a second location corresponding to the current location of the robot based on the second map data, based on a distance between the first location and the second location, the distance being smaller than a threshold distance, identify that the error does not exist in the second map data, and based on the distance between the first location and the second location, the distance being greater than or equal to the threshold distance, identify that the error exists in the second map data (See at least Artes Paragraph 115 “Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”).
Artes, however, fails to explicitly disclose that the at least one processor is further configured to: based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, and wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form.
Fu teaches that the at least one processor is further configured to:
based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, (See at least Fu Paragraph 87 “The clustering unit 415 may be configured to cluster the target unit regions into a plurality of groups based on the first data set and the second data set. Each group may include one or more target unit regions. In some embodiments, for a group including two or more target unit regions, differences between the parameters of any two of the two or more target unit regions are equal to or less than a parameter threshold, and the two or more target unit regions in the group may form a continuous region. For example, one of the plurality of groups may include three target unit regions, such as target unit region A, target unit region B, and target unit region C. The parameters of the three target unit regions may be a, b, and c, respectively. The differences (e.g., |a-b|, |a-c|, and |b-c|) between the parameters of any two of the three target unit regions are equal to or less than the parameter threshold, and the three target unit regions in the group may form a continuous region. It should be noted that the parameter threshold can be any reasonable value; it can be set according to experience (i.e. past data) . The current disclosure does not limit the specific process and specific value for setting the parameter threshold” |Paragraph 138 “For example, the clustering unit 415 may determine whether the difference between the parameters of the pending unit region and the start unit region is greater than a parameter threshold. In response to a determination that the difference between the parameters is equal to or less than the parameter threshold, which indicates that the termination condition is not met, the process 700 may proceed to 714 to determine an updated reference region by adding the pending unit region to the reference region. Then the clustering unit 415 may repeat operations 710-712 based on the updated reference region. In response to a determination that the difference between the parameters is greater than the parameter threshold, which indicates that the termination condition is met, the process 700 may proceed to 716.”) and
wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form (See at least Fu Paragraph 47 “An aspect of the present disclosure relates to systems and methods for region division related to an online to offline service. A target region may be divided into a plurality of target unit regions. For each target unit region, the server may determine predictive data (e.g., the number of service requests in a target unit region in the next 10 minutes) . The server may cluster the target unit regions into a plurality of groups based on the predictive data. Each of the plurality of groups may include one or more target unit regions. In the group that includes two or more target unit regions, the differences between the predictive data of any two of the two or more target unit regions may be less than a parameter threshold. The two or more target unit regions may form a continuous region. The server may divide the target region into a plurality of sub-regions based on the plurality of groups” | Paragraph 77 “In some embodiments, the target region may be divided, offline or online, into a plurality of unit regions that are bordering each other (i.e., without any gap) by the first obtaining unit 411. Information related to the plurality of unit regions in the target region may be stored in a storage medium (e.g., the storage device 150, the storage 220) . In some embodiments, the shape of the unit region may be circle, ellipse, polygon (e.g., triangle, quadrilateral, pentagon, hexagon) , arch, or the like. The shapes and/or sizes of the plurality of unit regions may be same or different. It should be noted that the above description about determining the unit regions is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure.”).
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 apparatus of Artes to include that the at least one processor is further configured to: based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, and wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form, as taught by Fu as disclosed above, in order to ensure optimal map updated (Fu Paragraph 4 “herefore, it is desirable to provide methods and systems to divide a target region rationally and efficiently, providing a basis for improvement of the O2O service”).
With respect to claim 5, and similarly claim 14, Artes in view of Fu teaches that the at least one processor is further configured to: compare first line information in the first map data and second line information in the second map data and generate a result of comparison, and identify whether the exists in the second map data based on the result of comparison (See at least Artes Paragraph 51 “FIG. 4 exemplarily illustrates orientation data 505 of a map 500 of a deployment area DA that a robot can use to orient itself and with the aid of which the robot can locate itself. As mentioned, such orientation data 505 can be collected by the robot itself, e.g. by means of sensors and can be compiled using a SLAM algorithm and entered into a map. For example, the robot measures the distance to obstacles (e.g. a wall, a piece of furniture, a door, etc.) by means of a distance sensor and calculates line segments from the measured values (usually a point cloud) that define the borders of its deployment area. The robot deployment area may be defined, for example, by a closed chain of line segments (polygonal line). Beyond this, there may be further obstacles located within the area of deployment that are represented in the orientation data. An alternative to the mentioned chain of line segments would be a raster map, in which a raster of cells (each measuring, e.g. 10×10 cm2) is laid over the robot deployment area and each cell is marked as either containing an obstacle or free of obstacles. A still further possibility would be to compile a map on the basis of image data recorded by a camera, wherein the image data is also linked to a location at which the image was taken. The image data can also be recognized by the robot and used to locate and orient itself in its environment.”).
With respect to claim 7, Artes in view of Fu teaches that the at least one processor is further configured to, based on identifying that a boundary line between the first region and the second region of the first map data and that the second map data is greater than or equal to a threshold length, update the first map data with the second map data (See at least Artes Paragraphs 135-138 “In order to compile the updated map 502, the changes to the deployment area in comparison to the point in time at which the already existing map 500 was compiled can be determined. For this, in particular the data regarding the structure of the environment that was recorded during the exploration and saved in a new temporary map and the orientation data contained in the existing map 500 (e.g. detected walls, obstacles and other landmarks) are compared. Alternatively or additionally, at the beginning of the exploration run a copy 501 of the permanently saved map 500 can be generated (in particular in the main memory of the processor 155), wherein the robot 100 determines its position in the copy (e.g. using the base station as a starting point or by means of global self-localization). During the renewed exploration the data in this work copy 501 can be directly updated, in the course of which, in particular, obstacles and/or landmarks no longer present are deleted, new obstacles and/or landmarks are added and recognized obstacles and/or landmarks are confirmed. After completion of the renewed exploration, the thus compiled work copy 501 can be compared to the still existing map 500. Alternatively or additionally, the data intended for deletion or addition can be directly utilized to determine what changes were made. When, for example, a newly identified obstacle is added to the map, the information that this obstacle was newly added can also be recorded (e.g. by marking it with a time stamp) … Additionally or alternatively, the floor covering of newly added surfaces can also be recorded. This can be carried out, for example, by measuring the floor covering borders and by utilizing the information regarding the floor covering already recorded in the map. It may happen, for example, that a user moves a wardrobe in a room or removes it from the room altogether. This creates a new surface area for the robot to which a floor covering can be assigned. If no floor covering border is detected in this area, the information regarding the floor covering of the surrounding area can be carried over onto the new surface area. If a floor covering border is detected, the floor covering of the new surface area can be automatedly determined or entered by the user. A cleaning program linked to the identified floor covering can then automatically be employed. Additionally or alternatively, a cleaning program specified for the surrounding area can also be carried over from the surrounding area onto the new surface area … If the dimensions of the carpet C (i.e. length, width and height) have remained unchanged, this information concerning the floor covering can be carried over from the previously existing map 500 into the updated map 502 and only the position data has to be updated. The carpet C may additionally be associated with a subarea created by the user. The position of this subarea can also be automatically updated to the new position of the carpet C, e.g. based on the floor covering borders.”).
With respect to claim 8, Artes in view of Fu teaches a display operatively connected to the at least one processor, wherein the at least one processor is further configured to: control the display to display a user interface inquiring a user instruction about whether to update the first map data with the second map data, and based on the user instruction received through the user interface, update the first map data with the second map data (See at least Artes Paragraph 170 “It may also happen, for example, that an accessible surface is detected that is not recorded in the map. The robot may conclude from this that the unmapped surface is a new subarea (a new room) and suggest to the user that it be explored in order to correspondingly update the existing map. Here it should be noted that a new accessible surface can also be created by leaving the entrance door to a house or apartment open. It may therefore be advisable for the robot to wait for a confirmation from the user before exploring the new subarea.”).
With respect to claim 9, Artes in view of Fu teaches a communication interface operatively connected to the at least one processor, wherein the at least one processor is further configured to control the communication interface to transmit the updated first map data to an external server (See at least Artes Paragraph 35 “Examples of external devices 300 include computers and servers onto which computations and/or data can be offloaded, external sensors that provide additional data or other household devices (e.g. other autonomous mobile robots) with which the autonomous mobile robot 100 can cooperate and/or exchange information.” | Paragraph 129 “The thus updated map 502 may now be permanently saved and used in further deployments of the robot for navigation and for interaction with the user. This makes it possible to completely replace the previously saved map 500. Additionally or alternatively, a backup of the map 500 can be retained. This can be stored, for example, on an external device 300 (e.g. a cloud server).”).
With respect to claim 10, Artes teaches a controlling method of a robot storing a map about a space, the map including first map data corresponding to a first region of the space, the controlling method comprising (See at least Artes Paragraph 135 “n order to compile the updated map 502, the changes to the deployment area in comparison to the point in time at which the already existing map 500 was compiled can be determined. For this, in particular the data regarding the structure of the environment that was recorded during the exploration and saved in a new temporary map and the orientation data contained in the existing map 500 (e.g. detected walls, obstacles and other landmarks) are compared. Alternatively or additionally, at the beginning of the exploration run a copy 501 of the permanently saved map 500 can be generated (in particular in the main memory of the processor 155), wherein the robot 100 determines its position in the copy (e.g. using the base station as a starting point or by means of global self-localization). During the renewed exploration the data in this work copy 501 can be directly updated, in the course of which, in particular, obstacles and/or landmarks no longer present are deleted, new obstacles and/or landmarks are added and recognized obstacles and/or landmarks are confirmed. After completion of the renewed exploration, the thus compiled work copy 501 can be compared to the still existing map 500. Alternatively or additionally, the data intended for deletion or addition can be directly utilized to determine what changes were made. When, for example, a newly identified obstacle is added to the map, the information that this obstacle was newly added can also be recorded (e.g. by marking it with a time stamp).”);
acquiring second map data while the robot is travelling in the space (See at least Artes Paragraph 33 “The human machine interface 200 can provide the user with information regarding the autonomous mobile robot 100, for example, in visual or acoustic form (e.g. loading status of batteries, present work task, map information such as a cleaning map, etc.)”);
based on the acquired second map data, comparing the first map data with the second map data; and based on identifying, as a result of the comparing the first map data and the second map data, that an error does not exist in the second map data and that the second map data comprises information on a second region, updating the first map data of the map with the second map data (See at least Artes Paragraph 123 “As an alternative, instead of deleting the map data, the problem area may again be explored. For example, the robot may recognize (as described above) that it is locked in in a given area, e.g. due to a door falling shut. In this case the robot would notify the user via the HMI 200 so that door, and with it the robot's path, can be opened, thus liberating the robot. Afterwards the user can tell the robot via the HMI 200 to carry on with the exploration. In such a case it may be useful for the problem area (that is, the room) to be, entirely or partially, explored again. The doorway (of the reopened door), for example, can now be recognized as freely accessible. The renewed exploration of the problem area may start from its edge or even be limited to its edge (e.g. locating and identifying the doorway).” | Paragraph 138 “The robot is capable of recognizing, for example, when floor covering borders have been moved, such as in the example from FIG. 12 involving the carpet C. If the dimensions of the carpet C (i.e. length, width and height) have remained unchanged, this information concerning the floor covering can be carried over from the previously existing map 500 into the updated map 502 and only the position data has to be updated. The carpet C may additionally be associated with a subarea created by the user. The position of this subarea can also be automatically updated to the new position of the carpet C, e.g. based on the floor covering borders”),
and based on identifying, based on the comparison result, that an error does not exist in the second map data and that the second map data comprises information on a second region, update the first map data with the second map data (See at least Artes Paragraph 139 “Danger zones linked to obstacles or objects can also be updated, for example. Further, a carpet C such as the one shown in FIG. 12 may also have a wide fringe that could become tangled in a rotating brush during cleaning. To avoid this, this side of the carpet can be marked in the original map 500 to be cleaned only with the brushes turned off. This metadata (e.g. saved in the map as an attribute of the subarea) can also be carried over to the new position of the carpet C. This means that metadata that concern the behavior or operation of the service unit 160 can also be automatically adapted to the updated subarea (which, in this example, is defined by the carpet C).”) and
travel the spacing using the map including the second map data (See at least Artes Paragraph 142 “The robot 100 may carry out a renewed exploration run through the deployment area DA and thereby expand the map such that the room R will be entered into the updated map so that it is taken into account and included in the planning of future deployments. When starting the renewed exploration run, the user can let the entire deployment area DA be newly explored and/or select a subarea for the exploration. For example, the user may send the robot 100 to a point before the opened door to room R. The robot would then begin exploring its environment starting at this point and would immediately recognize that the mapping of the deployment area is not yet complete. The robot recognizes that the room R lying behind the door is an accessible surface and will explore the room R in order to correspondingly expand the map. The new orientation data (i.e. the detected walls, obstacles and other landmarks) that concern the room R (including the information regarding the now open doorway) are then entered into the updated map 502. The remaining orientation data can be carried over unchanged into the updated map.”).
wherein the at least one processor is further configured to: based on identifying that the robot has a history of travelling in the second region based on the travelling history information of the robot update the first map data with the second map data (See at least Artes Paragraph 115 “Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”)
wherein the at least one processor is further configured to: identify a first location corresponding to a current location of the robot based on the first map data, identify a second location corresponding to the current location of the robot based on the second map data, based on a distance between the first location and the second location, the distance being smaller than a threshold distance, identify that the error does not exist in the second map data, and based on the distance between the first location and the second location, the distance being greater than or equal to the threshold distance, identify that the error exists in the second map data (See at least Artes Paragraph 115 “Here the robot may begin a global self-localization (FIG. 10, step S36), wherein the robot can determine its position relative to the already (partially) compiled map 500. The methods used for this are commonly known. For example, the robot may compile a new (temporary) map 501 and search for matches to the previously compiled map 500. If the matches are sufficiently definitive, the data from the temporary map 501 can be incorporated into the map 500 and the exploration run may be continued.”).
Artes, however, fails to explicitly disclose that the at least one processor is further configured to: based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, and wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form.
Fu teaches that the at least one processor is further configured to:
based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, (See at least Fu Paragraph 87 “The clustering unit 415 may be configured to cluster the target unit regions into a plurality of groups based on the first data set and the second data set. Each group may include one or more target unit regions. In some embodiments, for a group including two or more target unit regions, differences between the parameters of any two of the two or more target unit regions are equal to or less than a parameter threshold, and the two or more target unit regions in the group may form a continuous region. For example, one of the plurality of groups may include three target unit regions, such as target unit region A, target unit region B, and target unit region C. The parameters of the three target unit regions may be a, b, and c, respectively. The differences (e.g., |a-b|, |a-c|, and |b-c|) between the parameters of any two of the three target unit regions are equal to or less than the parameter threshold, and the three target unit regions in the group may form a continuous region. It should be noted that the parameter threshold can be any reasonable value; it can be set according to experience (i.e. past data) . The current disclosure does not limit the specific process and specific value for setting the parameter threshold” |Paragraph 138 “For example, the clustering unit 415 may determine whether the difference between the parameters of the pending unit region and the start unit region is greater than a parameter threshold. In response to a determination that the difference between the parameters is equal to or less than the parameter threshold, which indicates that the termination condition is not met, the process 700 may proceed to 714 to determine an updated reference region by adding the pending unit region to the reference region. Then the clustering unit 415 may repeat operations 710-712 based on the updated reference region. In response to a determination that the difference between the parameters is greater than the parameter threshold, which indicates that the termination condition is met, the process 700 may proceed to 716.”) and
wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form (See at least Fu Paragraph 47 “An aspect of the present disclosure relates to systems and methods for region division related to an online to offline service. A target region may be divided into a plurality of target unit regions. For each target unit region, the server may determine predictive data (e.g., the number of service requests in a target unit region in the next 10 minutes) . The server may cluster the target unit regions into a plurality of groups based on the predictive data. Each of the plurality of groups may include one or more target unit regions. In the group that includes two or more target unit regions, the differences between the predictive data of any two of the two or more target unit regions may be less than a parameter threshold. The two or more target unit regions may form a continuous region. The server may divide the target region into a plurality of sub-regions based on the plurality of groups” | Paragraph 77 “In some embodiments, the target region may be divided, offline or online, into a plurality of unit regions that are bordering each other (i.e., without any gap) by the first obtaining unit 411. Information related to the plurality of unit regions in the target region may be stored in a storage medium (e.g., the storage device 150, the storage 220) . In some embodiments, the shape of the unit region may be circle, ellipse, polygon (e.g., triangle, quadrilateral, pentagon, hexagon) , arch, or the like. The shapes and/or sizes of the plurality of unit regions may be same or different. It should be noted that the above description about determining the unit regions is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure.”).
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 method of Artes to include that the at least one processor is further configured to: based on identifying that the second region comprises a plurality of sub regions that are clustered and that a size of the second region is greater than or equal to a threshold size, update the first map data with the second map data, and wherein the plurality of sub regions are clustered based on the plurality of sub regions having a predetermined specification of a form, as taught by Fu as disclosed above, in order to ensure optimal map updated (Fu Paragraph 4 “herefore, it is desirable to provide methods and systems to divide a target region rationally and efficiently, providing a basis for improvement of the O2O service”).
Claims 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Artes (US 20220074762 A1) (“Artes”) in view of Fu (WO 2018223952 A1) (“Fu”) (Translation Attached) further in view of Chenjin (CN 105760811 A) (“Chenjin”).
With respect to claim 6, and similarly claim 15, Artes in view of Fu fails to explicitly disclose that the at least one processor is further configured to: acquire first histogram information based on angle information of lines in the first map data, acquire second histogram information based on angle information of lines in the second map data, based on similarity between the first histogram information and the second histogram information, the similarity being smaller than a threshold value, identify that the error does not exist in the second map data, and based on the similarity between the first histogram information and the second histogram information the similarity being greater than or equal to the threshold value, identify that the error exists in the second map data.
Chenjin teaches that the at least one processor is further configured to: acquire first histogram information based on angle information of lines in the first map data, acquire second histogram information based on angle information of lines in the second map data, based on similarity between the first histogram information and the second histogram information, the similarity being smaller than a threshold value, identify that the error does not exist in the second map data, and based on the similarity between the first histogram information and the second histogram information the similarity being greater than or equal to the threshold value, identify that the error exists in the second map data (See at least Chenjin Paragraphs 13-22 “A direction histogram is obtained according to the normal distribution frequency of the points in the scanned map point cloud. According to orthogonal projection, the scanned map point cloud is weightedly projected from discrete directions onto the line to obtain a projection histogram; Calculate the histogram correlation and quickly match the first local map and the second local map that are similar; Calculate the angle offset according to the direction histogram corresponding to the first local map and the second local map; Calculate the translation offset according to the projection histogram corresponding to the first local map and the second local map; synthesizing a first local map and a second local map according to an angle offset and a translation offset; Repeat the above steps until the global map is built. Furthermore, after obtaining the projection histogram, the method further comprises the steps of: An entropy sequence is obtained according to the normalized probability distribution of the projection histogram, the entropy sequence includes entropy measurement information of each angle projection line, and the angle offset is calculated according to the entropy measurement information. Furthermore, the method also includes the steps of performing correlation calculation based on the projection histograms corresponding to the first local map and the second local map, and recording the global peak value obtained in the correlation calculation, averaging the global peak values with the same angle offset, and arranging them in order to calculate the angle offset.”).
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 apparatus of Artes in view of Fu to include that the at least one processor is further configured to: acquire first histogram information based on angle information of lines in the first map data, acquire second histogram information based on angle information of lines in the second map data, based on similarity between the first histogram information and the second histogram information, the similarity being smaller than a threshold value, identify that the error does not exist in the second map data, and based on the similarity between the first histogram information and the second histogram information the similarity being greater than or equal to the threshold value, identify that the error exists in the second map data, as taught by Chenjin as disclosed above, in order to ensure that accurate maps are provided to the robot (Chenjin Paragraph 9 “This method proposes a closed-loop matching technology in global map matching technology, which can be applied to map matching in a global range.”).
Conclusion
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/IBRAHIM ABDOALATIF ALSOMAIRY/ Examiner, Art Unit 3667 /KENNETH J MALKOWSKI/Primary Examiner, Art Unit 3667