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 .
Response to Arguments/Amendments
The amendment filed February 9th, 2026 has been entered. Claims 2-27 are currently pending in the Application.
Applicant’s arguments with respect to the rejection of claims under 35 U.S.C 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 2-9, 12-13, 15-16, and 18-20, is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 20180361584, to Williams et al. (hereinafter Williams), and further in view of CN Patent Publication No. CN 102138769 A, to Song et al (hereinafter Song), and further in view of US Patent Publication No. 20140228999, to D'Andrea et al (hereinafter D'Andrea).
Regarding claim 2, and commensurate claim 19, Williams teaches A method, comprising: (a) obtaining a plurality of sensor data from a series of sensors disposed on a robot as the robot traverses one or more training trajectories in an environment; (See at least paragraph [0049] [0051-0052] “Navigation through service areas 140A-B may utilize a combination of digital map usage (e.g., localization determined based on navigation through the mapped area) and real-time sensors (e.g., sensors 104 monitoring the robotic platform's surrounding environment). In addition, RF locator nodes 150A-C may be used to navigate and localize,”).
(b)determining, by the robot, a cleaning area in the environment by: (See at least paragraph [Abstract] “a robotic device comprising a propulsion mechanism to move the robotic device, a sensor for sensing objects, a position sensor, a localization and mapping system,”)
(c) identifying grids within the grid map of one or more target areas to clean within the cleaning area based on a designation of one or more boundaries for the one or more target areas in the grid map, wherein the one or more boundaries are recorded by the robot as the robot traverses or moves along the one or more boundaries; (See at least paragraph [0140] “the user may have the robotic platform 100 follow them along a path 3902 around the perimeter of the room (e.g., teaching the robotic platform 100 the wall boundaries by guiding it along the edge of the walls, or around any selected area), and then instruct the robotic platform 100 to clean the area within the defined area.”)
and (d) controlling movement or navigation along one or more cleaning paths through or within the one or more target areas to clean the one or more target areas or a portion thereof. (See at least paragraph [0140] “the robotic platform 100 uses the list of previously recorded positions and orientations as way points for navigation functionality. In both the fill mode and teach-repeat mode (as described herein) the robotic platform 100 may use its sensors 104 to continuously determine and update its location and orientation.”)
William fails to explicitly disclose, however Song discloses, (i)projecting the plurality of sensor data obtained from the one or more training trajectories onto a grid map; (See [Page 7, Paragraph 8-10] “It is the grid that entire environment is divided into some identical sizes that rasterizing is handled, and points out wherein whether to exist barrier for each grid.Grating map is easy to create and safeguard, the information of each grid that clean robot is understood is directly corresponding with certain zone in the environment, use ultrasonic wave or the so cheap sensor of infrared ray can obtain to create the information of map and add in the map, by means of this map, can carry out self-align and path planning easily.So, the map that adopts rasterizing to handle in the present embodiment. Map adopts gridding to be about to the discretization of coordinate, and the real area by cleaning and the mapping of grid area realize that the discretization of actual physics purging zone represents. In map, the grid that is occupied wholly or in part by barrier is designated as not cleanable area, does not have the grid of barrier to be regarded as cleanable area fully.The quantity of state that each grid is corresponding one three, it is data of having described this regional situation, i.e. (i, j, k) (i wherein, j) represented the position of grid, in the described preset rules, k 0 has represented unknown zone, and k 1 has represented the zone that can clean, k 2 represents wall or along the wall obstacle information, and k 3 represents isolated danger information.Clean robot is carrying out in the study of limit, and control system can all be obtained a real-time location parameter, x coordinate, y coordinate, the line item of going forward side by side in each sampling period from navigation system.The all back data to record of having walked are handled, and extract x , x , y , y Thereby the cleaning environment of arbitrary shape can be Max Min Max Min defined as a long x of being -x , wide is y -y Rectangular model.Clean robot cleans along the direction of rectangular model Max Min Max Min longer sides when carrying out the winding type cleaning.Following formula can be expressed the physical location parameter, and (x is y) with grid position parameter (i, j) correlation between”)
(ii) identifying a position and a size of one or more obstacles from the plurality of sensor data; (See [Page 9, Paragraph 1-2] “g.Start the obstacle program after running into barrier, the obstacle thing takes a round in the counterclockwise direction, the obstacle thing take a round can the disturbance in judgement thing shape and size, for cartographic information and path planning provide more Useful Informations, Fig. 6 is a path planning behind the unknown obstacle for robot inquires the place ahead. When walking, also sets up the obstacle thing barrier grating map information, position and the size information of barrier in grating map just can have been come out in concrete manifestation like this, utilize the current position in grid of coordinate information inquiry robot earlier, promptly calculate (i, j, k) i in, j is changed to 3 to the k value of correspondence then, represents current grid to be occupied by barrier, the obstacle thing takes a round back map update mode as shown in Figure 7, and the current grid of latticed expression is an isolated danger among the figure.Extreme value that can dyscalculia thing border in obstacle thing process, the maximum of barrier coordinate and minimum of a value x , y , x , y These information provide certain reference value can for later path planning, as can be seen Min Min Max Max from Figure 7 setting up cartographic information obstruction size like this is exaggerated, the path planning of robot point-to-point leaves surplus after can giving like this, and has also remedied the influence that the error that the robot location causes causes path planning so to a certain extent.”). Further, (See [Abstract] “acquiring position and outline data by surrounding the isolated obstacle”)
(iii) projecting the one or more obstacles onto the grid map based on the identified position and size of each obstacle; (See [Page 7, Paragraph 8-10] “It is the grid that entire environment is divided into some identical sizes that rasterizing is handled, and points out wherein whether to exist barrier for each grid.Grating map is easy to create and safeguard, the information of each grid that clean robot is understood is directly corresponding with certain zone in the environment, use ultrasonic wave or the so cheap sensor of infrared ray can obtain to create the information of map and add in the map, by means of this map, can carry out self-align and path planning easily.So, the map that adopts rasterizing to handle in the present embodiment. Map adopts gridding to be about to the discretization of coordinate, and the real area by cleaning and the mapping of grid area realize that the discretization of actual physics purging zone represents. In map, the grid that is occupied wholly or in part by barrier is designated as not cleanable area, does not have the grid of barrier to be regarded as cleanable area fully.The quantity of state that each grid is corresponding one three, it is data of having described this regional situation, i.e. (i, j, k) (i wherein, j) represented the position of grid, in the described preset rules, k 0 has represented unknown zone, and k 1 has represented the zone that can clean, k 2 represents wall or along the wall obstacle information, and k 3 represents isolated danger information.Clean robot is carrying out in the study of limit, and control system can all be obtained a real-time location parameter, x coordinate, y coordinate, the line item of going forward side by side in each sampling period from navigation system.The all back data to record of having walked are handled, and extract x , x , y , y Thereby the cleaning environment of arbitrary shape can be Max Min Max Min defined as a long x of being -x , wide is y -y Rectangular model.Clean robot cleans along the direction of rectangular model Max Min Max Min longer sides when carrying out the winding type cleaning.Following formula can be expressed the physical location parameter, and (x is y) with grid position parameter (i, j) correlation between”)
(iv)assigning, to each grid in the grid map, a value indicating a likelihood that each grid is traversable; and (See [Page 7, Paragraph 8] “, k 0 has represented unknown zone, and k 1 has represented the zone that can clean, k 2 represents wall or along the wall obstacle information, and k 3 represents isolated danger information”)
(v) identifying a cleaning area in the environment by identifying grids in the grid map that comprise values indicating that the grid is traversable: (See [Page 8, Paragraph 3] “in described map boundary line, travel through first in default traversal mode, then obtain its position and outline data if run into isolated danger around this isolated danger, and utilize this position and outline data and described data boundary, in described map boundary line, identify cleanable area;”)
processing vision data included in the plurality of sensor data to identify a marker in the environment, wherein the marker has a series of values specifying a position of the marker in a grid map; deriving an initial position of the robot based on a distance between the robot and the marker as indicated in the vision data; (See at least paragraph [0060-0062] “Additionally, the location of inventory holder 30 relative to mobile drive unit 20 may shift during transit. As a result, the location of inventory holder 30 may not be properly aligned with fiducial marker 50b after undocking despite any steps taken by mobile drive unit 20 to align itself to fiducial marker 50b. Moreover, in particular embodiments, mobile drive units 20 may use the expected location of inventory holders to navigate within the workspace of inventory system 10. As a result, if inventory holder 30 is left at the requested destination without being properly aligned with fiducial marker 50b, other mobile drive units 20 may interfere with inventory holder 30, other mobile drive units 20 may subsequently have difficulty docking with inventory holder 30, and/or other related problems may arise. Consequently, mobile drive unit 20 may attempt to verify that inventory holder 30 is properly aligned with fiducial mark 50b and, if not, take appropriate steps to align inventory holder 30 with fiducial mark 50b.For example, in particular embodiments, mobile drive unit 20 may, after undocking from inventory holder 30 determine a location of inventory holder 30. Mobile drive unit 20 may utilize holder sensor 150 to detect the location of inventory holder 30. Based on the information detected by holder sensor 150, mobile drive unit 20 may determine the difference between the location of mobile drive unit 20 and the location of inventory holder 30. If the difference is greater than some predetermined tolerance, mobile drive unit 20 may attempt to move inventory holder 30 to more closely align inventory holder 30 with the current location of mobile drive unit 20 and/or fiducial mark 50b, as shown in FIGS. 4F-4H. FIGS. 4F-4H illustrate operation of a particular embodiment of mobile drive unit 20 after determining that the location of inventory holder 30 differs from the location of mobile drive unit 20 and/or fiducial mark 50b by more than the predetermined tolerance. More specifically, FIG. 4F illustrates mobile drive unit 20 as mobile drive unit 20 positions itself under inventory holder 30. In particular, after determining that the location of inventory holder 30 differs from the current location of mobile drive unit 20 and/or that of fiducial mark 50b by more than the predetermined tolerance, mobile drive unit 20, in the illustrated embodiment, moves to a new location based on the detected location of inventory holder 30, as shown by arrow 530. In the illustrated embodiment, mobile drive unit 20 repositions itself so that holder sensor 150 is located under holder identifier 360. Mobile drive unit 20 then docks with inventory holder 30 again in a similar manner to that shown in FIG. 4C. “)
Williams as modified by Song, and D'Andrea are analogous art because they are in the same field of endeavor, autonomous mobile robots. 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 William to incorporate the teachings of Song such that identifying cleanable grids vs non cleaning grids of Song will aid in navigating the robot of William to effectively understand and clean the areas required to be cleaned. Further incorporating the and vision-based marker system of D'Andrea. William teaches autonomous cleaning system that relies on active RF locators nodes to resolve spatial and localization of the robot, therefore a person of ordinary skill in the art will recognize that RF based localization in indoor settings is not the best due to signal fading and interference from metal structures, therefore implementing visual markers that encode their precise grid map coordinates as taught by D'Andrea provides a highly accurate position system which will aid William robot with error free method to derive exact positions.
Regarding claim 3, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, wherein the one or more training trajectories define or span a portion of the potential cleaning area. (See at least paragraph [0157] “Through this action the robotic platform 100 may create a quick map of the selected area 4502 and determine the physical bounds (e.g., boundary conditions) and obstacles within the selected area 4502”)
Regarding claim 4, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, wherein the sensor data indicates a position or an orientation of the one or more obstacles. (See at least paragraph [0055] “the robotic platform determined that the obstacle was a static obstacle and stored its location for possible later re-treatment”)
Regarding claim 5, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising, in (a), capturing the sensor data while the robot is manually pushed along the one or more training trajectories. (See at least paragraph [0147] “a user may enable the teaching portion 4202 of the teach-repeat mode for the robotic platform 100, such as through a graphical user interface (e.g., on the robotic platform 100, through a remote mobile interface, and the like), and manually direct the robotic platform 100 around a service area.”)
Regarding claim 6, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, wherein the one or more boundaries for the one or more target areas are designated by a user or an operator of the robot. (See at least paragraph [0148] “the user is able to teach the robotic platform 100 to learn any path that that user desires. For example, the user may teach the robotic platform 100 the outer perimeter of a room by walking the robotic platform 100 along the outer wall, such as in path 3902, providing precise pose and positioning of the robotic platform 100, and then, in the repeat mode, specify that the robot clean the room as defined by the established path, where the robotic platform 100 cleans the outer defined path 3902 as well as all surfaces within the bounded space (e.g., the area bounded by the closed path). In embodiments, the ‘bounded space’ may be determined by a closed path, by an open path where the robotic platform 100 calculates the bounded space from the open path geometry, and the like.”)
Regarding claim 7, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising, in (a), registering or recording one or more coordinates for the one or more boundaries on the map as the robot is manually pushed along the one or more training trajectories. (See at least paragraph [0146] “As the robotic platform 100 is being taught a path, e.g. being directed along a specific path by an operator, the teach-repeat facility 4102 periodically records and stores the pose information in a file. ”)
Regarding claim 8, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, wherein the one or more target areas are identified by excluding an area in the environment in which the one or more obstacles are located. (See at least paragraph [0148] “obstacles to avoid”)
Regarding claim 9, William as modified by Song, and D'Andrea disclose the claimed features of claim 9 and further disclose, wherein the one or more target areas are identified by excluding an additional area in the environment that is proximal or adjacent to the area in which the one or more obstacles are located. (See at least paragraph [0148] “stay-out areas, obstacles to avoid, edges to stay clear of, and the like, may also be defined such that the robotic platform 100 cleans only the intended areas.”)
Regarding claim 12, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising, in (c), cleaning the one or more target areas while avoiding one or more obstacle areas comprising the one or more obstacles detected by the robot. (See at least paragraph [0148] “where the robotic platform 100 cleans the outer defined path 3902 as well as all surfaces within the bounded space (e.g., the area bounded by the closed path). In embodiments, the ‘bounded space’ may be determined by a closed path, by an open path where the robotic platform 100 calculates the bounded space from the open path geometry, and the like.”)
Regarding claim 13, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, wherein the one or more target areas comprise two or more target areas designated by two or more distinct boundaries. (See at least paragraph [0151-0152] “the robotic platform 100 may utilize teach-repeat capabilities to map and plan for the cleaning of a series of service areas as part of a service plan, where the robotic platform 100 is first brought into a first service area, such as by manual control or through “follow-me” functionality. The transition from a parked location to a start position for the first service area may also be taught to the robotic platform 100, so that an automated service plan may begin at the parked location (e.g., starting the service plan at the charging station). Once at the starting location for the first service area, the teach-repeat mode is utilized to teach the robotic platform 100 the boundary of the area through making a closed path. For instance, a user may walk the robotic platform 100 around the wall edges as part of teaching the robotic platform 100 the bounds of the first service area. The robotic platform 100 utilizes mapping functionality, such as a SLAM algorithm, to generate a map of the first service area. The process is then repeated for subsequent service areas, with optional teaching associated with transitions between different service areas, through floor transitions, and with resource and/or charging station stops, including the endpoint of the service plan. This example is not meant to be limiting in any way but illustrates some of the capabilities for planning and mapping that may be utilized through the teach-repeat facility.”)
Regarding claim 15, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising, in (a), partitioning the target area into two or more sub-areas for cleaning. (See at least paragraph [0148] “a user may be able to directly build (e.g., in real-time, into a database) a new map for a service area, where the robot then knows where to start, where-how to service, where not to service, what to avoid, and the like. The robotic platform 100 may also be taught an irregular path to follow, where it follows any path line determined by the user (e.g., following an irregularly shaped stain along the floor, moving from sub-area to sub-area within a service area (e.g., areas of a room that always seem to get especially dirty), and the like.”)
Regarding claim 16, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising expanding the one or more training trajectories based on the sensor data obtained by the robot. (See at least paragraph [0170] “update the digital map to identify the object at the second location (e.g., updating the digital map for the new location of the table).”)
Regarding claim 18, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and further disclose, further comprising adjusting or expanding the one or more training trajectories based on a processing of the sensor data using artificial intelligence (AI) or machine learning (ML). (See at least paragraph [0114] “the robotic platform 100 may provide for machine learning adaptive service plan tasking, such as the robotic platform 100 adjusting its plan tasking (e.g., from day to day) based on what it has learned from past service executions.”)
Regarding claim 20, William as modified by Song, and D'Andrea discloses the claimed features of claim 19 and further disclose, further comprising providing the one or more maps to the plurality of robots when the plurality of robots register or image the one or more scannable objects. (See at least paragraph [0179] “A central repository may provide program instructions to be executed on different devices.”)
Claims 10-11, 14,17, and 21-27 is/are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Publication No. 20180361584, to Williams et al. (hereinafter Williams), and further in view of CN Patent Publication No. CN 102138769 A, to Song et al (hereinafter Song), and further in view of US Patent Publication No. 20140228999, to D'Andrea et al (hereinafter D'Andrea), and further in view of WIPO Patent Publication No. WO 2019126332A, to Herman et al (hereinafter Herman).
Regarding claim 10, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and William does not explicitly disclose, however Herman discloses, wherein the map comprises (i) one or more obstacle areas comprising the one or more obstacles detected by the robot and (ii) one or more transitable areas comprising the one or more training trajectories. (See at least paragraph [0109] “maps may also include a path defined as a sequence of locations and uncertainties between locations. This is different than a grid defining the robot path.”) Further, (See at least paragraph [0105] “updates both free and occupied cells in occupancy maps.”).
Williams as modified by Herman, are analogous art because they are in the same field of endeavor, robotic cleaning 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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman such that will aid in the teachings in William for the purposes of detecting many obstacles in a area and understand the cleaning sequence.
Regarding claim 11, William as modified by Song, and D'Andrea disclose the claimed features of claim 2 and William does not explicitly disclose, however Herman discloses, wherein the map comprises an occupancy grid. (See at least paragraph [0109] “maps may also include a path defined as a sequence of locations and uncertainties between locations. This is different than a grid defining the robot path.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 14, William as modified by Song, and D'Andrea disclose the claimed features of claim 13 and William does not explicitly disclose, however Herman discloses, wherein the two or more target areas are merged into a combined target area for the robot to clean. (See at least paragraph [0099] “The regional map 194 is then added to the global map 195 and to the global graph, which represents regional maps, their positions, and constraints. The global map 195 is rebuilt by combining the regional maps 194 using the updated global graph information.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 17, William as modified by Song, D'Andrea, and Herman disclose the claimed features of claim 16 and William does not explicitly disclose, however Herman discloses, wherein the one or more expanded trajectories permit the robot to traverse a path that extends beyond the one or more training trajectories. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 21, William as modified by Song, and D'Andrea discloses the claimed features of claim 20 and William does not explicitly disclose, however Herman discloses, wherein the one or more maps comprise a plurality of different maps. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 22, William as modified by Song, D'Andrea and Herman discloses the claimed features of claim 21 and William does not explicitly disclose, however Herman discloses, wherein the plurality of different maps are provided to different robots of the plurality of robots. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 23, William as modified by Song, D'Andrea and Herman discloses the claimed features of claim 21 and William does not explicitly disclose, however Herman discloses, wherein the plurality of different maps comprise different trajectories for different robots. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 24, William as modified by Song, D'Andrea and Herman discloses the claimed features of claim 21 and William does not explicitly disclose, however Herman discloses, wherein the plurality of different maps correspond to different regions or sub-areas of the environment. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 25, William as modified by Song, D'Andrea and Herman discloses the claimed features of claim 21 and William does not explicitly disclose, however Herman discloses, wherein the plurality of robots are configured to collectively perform the one or more tasks. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
Regarding claim 26, William as modified by Song, D'Andrea and Herman discloses the claimed features of claim 21 and William discloses, wherein the plurality of robots are configured to independently perform the one or more tasks. (See at least paragraph [0179] “A central repository may provide program instructions to be executed on different devices.”).
Regarding claim 27, William as modified by Song, and D'Andrea discloses the claimed features of claim 19 and William does not explicitly disclose, however Herman discloses, wherein the plurality of robots are configured to share the one or more maps of the environment. (See at least paragraph [0108] “An example of a global map as shown in FIG. 16 and may be broken down into several regional maps l94a... 194h. Preferably, each regional map l94a ... 194h is globally referenced to the same coordinate frame, so as to reference different region maps to each other. The global path planning plans the path of the robot between regions l94a ... 194h, while the regional path planning plans the path of the robot within each regional map l94a ... 194h. Local path planning plans the path of the robot within the vicinity of the robot within each region. Global planning can be accomplished by combining all of the region maps into a single global map 195.”)
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 William as modified by Song, and D'Andrea to incorporate the teachings of Herman for the same motivation reasons in claim 10.
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