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 .
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.
Joint Inventors
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Response to Arguments and Amendments
Applicant’s arguments and amendments, filed August 11th, 2026, with respect to the rejections of claims 1-6, 8, 12-14, 16-17 and 19-21 under 35 U.S.C. 103 have been fully considered and they persuasive. However, upon further search and consideration, a new ground(s) of rejection is made in view of Criswell (US Patent Pub. No. 2019/0315582 A1) as shown in the 103 rejections below.
Examiner notes that in the Applicant-Initiated Interview held on August 11th, 2026, discussions were made regarding the necessitation of the ceiling of a container being the obstacle for consideration when determining collision avoidance functionalities of the robot arm/end-effector. Examiner suggested adding clarification for specifically necessitating collision avoidance at or near the ceiling. While the additional limitations in the amendments are sufficient to overcome the prior combination of art, it is still much too broad to be found as a novel improvement on the existing available art (as seen in the additional reference below) because they are only claiming the ceiling “being within reach” of the robot and nothing more. Furthermore, Examiner notes the amendments involving a “geometry” of the ceiling are more descriptive than the prior limitations of “ceiling estimate”, but are still too broad to overcome any art directed towards generic surface mapping and distance estimation in mobile robotics.
For at least for the reasons stated above, the 35 U.S.C. 103 rejections have been updated below to address amended limitations.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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 1-6, 8, 12-14, 16-17, and 19-21 are rejected under 35 U.S.C. 103 as being obvious over Watts (US Patent No. 9,632,504 B1) in view of Criswell (US Patent Pub. No. 2019/0315582 A1) and Pardi et al. (“Maximally Manipulable Vision-Based Motion Planning for Robotic Rough-Cutting on Arbitrarily Shaped Surfaces”), herein “Pardi”.
Regarding Claim 1, Watts discloses a method of avoiding a collision between a mobile robot and a ceiling of a container within which the mobile robot is configured to operate (See Fig. 4C below and Col. 3 Lines 47-58, “[…] a robotic device may use contours of a surface of a building, such as a ceiling, to help with localization. In particular, the ceiling of a building in which the robotic device is operating may have varying depth texture, which may include different shapes, structures, and/or patterns […] a robotic device may perform warehouse operations requiring navigation within a warehouse that contains a ceiling […] may be used to help a robotic device determine its precise location within the building.”), the method comprising:
sensing distance measurement data associated with the ceiling of the container using one or more distance sensors arranged on an end effector of the mobile robot (See Fig. 2A and 4C below, and also Col. 4 Lines 1-30, “The initial contour map may be generated using one or more depth sensors […] a mapping robot may be assigned to navigate through the building with a stereo camera that collects depth images of the ceiling at different points […] sensor devices that provide enough distance measurements from the robot to different points on the ceiling to identify one or more of the surface contours.” See also Col. 10 Line 67 to Col. 11 Lines 1-4, “[…] may use one or more sensors attached to a robotic arm 202, such as sensor 206 and sensor 208, which may be two-dimensional (2D) sensors and/or 3D depth sensors […]”);
determining an estimate of a geometry of the ceiling of the container based on the distance measurement data (See Col. 4 Lines 55-63, “[…] the robot may be able to use a rough estimate of its current position to determine a relatively small search area on the map of ceiling contours to look for matching contours […] first determining a rough estimate of the robot's location […] collect the sensor data for identifying ceiling contours.”).
wherein controlling the arm of the mobile robot and/or the end effector of the mobile robot comprises controlling the arm and/or the end effector to move without colliding with the ceiling of the container (See Col. 10 Lines 49-52, “[…] reconstructed environment may then be used for identifying objects to pick up, determining pick positions for objects, and/or planning collision-free trajectories for the one or more robotic arms and/or a mobile base.”).
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But does not explicitly disclose the ceiling of the container being within reach of an arm of the mobile robot and/or the end effector coupled to the arm of the mobile robot; and
controlling the arm of the mobile robot and/or the end effector of the mobile robot based, at least in part, on the estimate of the geometry of the ceiling of the container.
Criswell, in a similar field of endeavor, teaches the ceiling of the container being within reach of an arm of the mobile robot and/or the end effector coupled to the arm of the mobile robot (See Fig. 1 shown below and 0051-0052, “[…] When beginning a removal operation, the automatic truck unloader 10 identifies a product space, e.g., space of boxes 46A through 46S, including a product skyline 330 and chooses an active quadrant 332 to begin […] unloading and unpacking continues in the active quadrant 332 at newly defined skyline 332 with the removal of box 46A, then 46C. As the product space diminishes, the active quadrant is readjusted and within each new skyline […]” See also 0057, “[…] automatic truck unloader is positioned proximate to the row of boxes 344 j such that the removal of boxes 46 within the trailer 16 may begin and the boxes 46 are within the reachable space 132 of the industrial robot […] selective articulated movement through the reachable space 132, the industrial robot 56 removes the boxes 46 from the trailer and sequentially selects the box to be removed based on how far particular boxes in an active quadrant protrude.” Examiner notes Fig. 1 clearly shows the robot arm/end effector is within reach of the ceiling, necessarily when executing an operation on products on top of the stack)
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Pardi, in a similar field of endeavor, teaches controlling the arm of the mobile robot and/or the end effector of the mobile robot based, at least in part, on the estimate of the geometry of the ceiling of the container (See Abstract, “[…] method for constrained motion planning from vision, which enables a robot to move its end-effector over an observed surface, given start and destination points […] finding robot trajectories which maximize the robot’s manipulability throughout the motion, while also minimizing surface-distance travelled between the two points.” Examiner notes the motion planner uses visual surface observation to generate trajectories for the robot’s end-effector over an arbitrary surface, with emphasis on surface-based planning).
In view of Criswell and Pardi’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the mobile robot measuring distances to building surfaces including ceilings and using representations of such surfaces for navigation, localization, and motion planning within a container or building environment as disclosed by Watts, the ability to use the distance measurements to generate and control trajectories of the robot’s arm or end-effector including reachable space near the ceiling, with a reasonable expectation of success, since each robot relies on sensor-derived surface estimates and their combination predictably improves safety and motion planning in confined robotic environments.
Regarding Claim 2, Watts further discloses the method of claim 1, wherein the one or more distance sensors include a first distance sensor arranged on a first side of the end effector, the first distance sensor being configured to sense a first distance in a first direction (See Fig. 4C above and Col. 16 Lines 18-20, “[…] a first sensor 452 on the robot 450 may detect a number of points 464 as the first sensor 452 is directed at a particular orientation towards the ceiling 400.”), the method further comprising:
orienting, prior to sensing the distance measurement data, the first distance sensor such that the first direction is toward the ceiling of the container (See Fig. 4C and Col. 16 Lines 18-20 as referenced above).
Regarding Claim 3, Watts further discloses the method of claim 2, wherein the one or more distance sensors include a second distance sensor arranged on a second side of the end effector, the second distance sensor being configured to sense a second distance in a second direction, the second direction being opposite the first direction (See Fig. 4C above and Col. 16 Lines 34-48, “[…] a second sensor 454 on robot 450 may detect a separate set of points 462 while the second sensor 454 is oriented in a different direction towards ceiling 400.”),
wherein sensing distance measurement data comprises sensing distance measurement data including the first distance and the second distance (See Col. 16 Lines 38-41, “By orienting the second sensor 454 in a different upward direction, additional data points may be collected to identify additional contours for more precise localization.” Examiner notes the collection of “additional” contours to increase measurement precision means both the data from the first sensor and second sensor are being used together).
Regarding Claim 4, Watts further discloses the method of claim 2, wherein sensing distance measurement data comprises:
controlling the arm of the mobile robot to move the arm through a scan trajectory (See Col. 10 Lines 43-52, “The sensors may scan an environment containing one or more objects in order to capture visual data and/or three-dimensional (3D) depth information. Data from the scans may then be integrated into a representation of larger areas in order to provide digital environment reconstruction […] planning collision-free trajectories for the one or more robotic arms and/or a mobile base.” See also Col. 11 Lines 9-18, “[…] scans from one or more 2D or 3D sensors with fixed mounts on a mobile base, such as a front navigation sensor 216 and a rear navigation sensor 218, and one or more sensors mounted on a robotic arm, such as sensor 206 and sensor 208, may be integrated to build up a digital model of the environment, including the sides, floor, ceiling, and/or front wall of a truck or other container. Using this information, the control system may cause the mobile base to navigate into a position […]” Examiner notes the sensors on the robot arm scan the environment while operating and are able to integrate the information into trajectories for the mobile base or robot arm); and
sensing the distance measurement data as the arm is moved through the scan trajectory (See Col. 10 Lines 43-52 and Col. 11 Lines 9-18 as referenced above).
Regarding Claim 5, Watts further discloses the method of claim 4, wherein controlling an arm of the mobile robot to move the arm through a scan trajectory comprises moving the arm through a scan trajectory that includes a first direction and a second direction at an angle to the first direction (See Col. 15 Lines 4-12, “[…] a mobile robot may collect data from one or more sensors directed towards the surface as the robot is operating. Different types and numbers of sensors may be used […] the robot use may two or more fixed depth sensors oriented in different directions to provide different views of the surface for collection of depth data. For instance, a robot may be equipped with three laser rangefinders angled upward in order to collect data from different areas on the ceiling.” See also Col. 5 Lines 3-9, “[…] a robot may be equipped with one or more upward facing sensors that can change orientation when their view of the ceiling is obstructed as well […] one or more of the upward facing sensors may also periodically or continuously change orientation as the robot operates to collect more ceiling contour data for precise navigation.” Examiner notes the sensors on the robot arm able to continuously change orientation as the robot operates means it is capable of moving the arm through a scan trajectory including multiple directions at different angles).
Regarding Claim 6, Watts further discloses the method of claim 5, wherein the scan trajectory includes a first segment along the first direction, a second segment along the first direction, and a third segment along the second direction, the third segment connecting the first and second segments (See Col. 16 Lines 58-67 to Col. 17 Lines 8-39, “[…] contours in different areas on the ceiling or other surface may each be identified from sensor data collected by the robot from the different areas. Identifying multiple contours may provide improved precision as well as redundancy. Multiple contours may also enable accurate localization when the surface has certain repeating contours (e.g., resulting from a number of identical features that are positioned at multiple points on the surface) […] one contour corresponds to the outer boundary of lighting fixture 408. In this case, a contour line around the edge of lighting fixture 408 indicates both the area covered by the lighting fixture 408 on the depth map as well as the depth difference between lighting fixture 408 and the ceiling 400 directly above it. The contour line includes points of equal depth around the circle […] A surface contour follows this shape from one edge of the light to the other. Contours showing the changing surface depth from the lighting fixture 408, including the area, surface curves, and/or depth difference from the ceiling, may be used in order to align the detected points 464 at a position which corresponds to the contours on the depth map […] one contour corresponds to the outer boundary of air duct 402. A contour line around the boundary of air duct indicates both the width spanned by the air duct 402 on the depth map as well as the depth difference between air duct 402 and the ceiling 400 directly above it […] including the width, surface curves, and/or depth differences, may be used in order to align the detected points 462 at a position which corresponds to the contours on the depth map.” Examiner notes all the reference points collected with the sensors are aligned by connecting various segments of contours shown on the depth map. Each segment represents a distance/depth collected by a scan, and there exists multiple segments collected in multiple directions of the environment with reference to the ceiling above the detected area).
Regarding Claim 8, Watts further discloses the method of claim 1, wherein determining an estimate of a geometry of the ceiling of the container based on the distance measurement data comprises:
fitting a plane based on at least one datum in the distance measurement data (See Col. 13 Lines 35-57, “[…] depth map includes indications of depth at different points on the surface […] A surface contour includes a group of connected points on the surface representative of the depth of the surface at each of the points. More specifically, surface contours represent depth outlines of one or more features of a surface of the building. Surface features with irregular or curving shapes may be particularly helpful for robotic localization […] some of the contours may correspond to components attached to the surface […] some of the contours may correspond to the shape of the surface itself […] a building may have a curved or arching ceiling, or a ceiling with two or more planes aligned at different angles to one another. Some of the contours may be connected points with the same depth (e.g., the outline of the outer edge of a ceiling light). Other contours may be connected points with depth that changes in a linear way, or according to some predictable function (e.g., a part of a ceiling that curves with a consistent degree of curvature).” Examiner notes the measurement data takes into account the possibility of either a single plane or multiple planes to represent the surface contour of the ceiling, hence the generation of a depth map showing outlines at different points on the surface that may include more than one plane or other protruding shapes and features); and
determining the estimate of the geometry of the ceiling of the container based on the plane (See Col. 4 Lines 55-63 and Col. 13 Lines 35-57 as referenced above).
Regarding Claim 12, Watts further discloses the method of claim 8, wherein fitting a plane comprises fitting a flat plane to the at least one datum (See Col. 4 Lines 55-63 and Col. 13 Lines 35-57 as referenced above. Examiner notes the surface of the ceiling is the datum, and a flat ceiling is the same as fitting a flat plane to the datum since the robot is able to determine the surface to be lacking contours or depth).
Regarding Claim 13, Watts further discloses the method of claim 8, wherein fitting a plane comprises fitting a curved plane using at least two pieces of data of the distance measurement data (See Col. 13 Lines 49-57, “[…] may have a curved or arching ceiling, or a ceiling with two or more planes aligned at different angles to one another. Some of the contours may be connected points with the same depth (e.g., the outline of the outer edge of a ceiling light). Other contours may be connected points with depth that changes in a linear way, or according to some predictable function (e.g., a part of a ceiling that curves with a consistent degree of curvature).” See also Col. 17 Lines 20-25, “Contours showing the changing surface depth […] including the area, surface curves, and/or depth difference from the ceiling, may be used in order to align the detected points 464 at a position which corresponds to the contours on the depth map.” Examiner notes the degrees of curvature and angular alignment of two or more planes relative to each other are two pieces of data regarding a curved plane).
Regarding Claim 14, Watts further discloses the method of claim 8, wherein determining an estimate of a geometry of the ceiling of the container based on the distance measurement data further comprises assigning a shape primitive to the plane (See Col. 14 Lines 42-44, “[…] some contours may be identified within the depth map based on the shape or curvature of individual components or groups of connected components.” See also Col. 16 Lines 52-65, “[…] detected points that fall within one or more contours stored in the map may be identified by looking for matching shapes, curves, and/or changes in depth […] just one uniquely identifiable surface contour may be identified from sensor data and used to align the position of the robot with the depth map […] Identifying multiple contours may provide improved precision as well as redundancy. Multiple contours may also enable accurate localization when the surface has certain repeating contours (e.g., resulting from a number of identical features that are positioned at multiple points on the surface).”), and
controlling at least one operation of the mobile robot based, at least in part, on the shape primitive (See Col. 14 Lines 42-44 and Col. 16 Lines 52-65 as referenced above. Examiner notes controlling the robot to align with the depth map based on the shape or curvatures in the detected surface contour(s) is controlling an operation of the mobile robot).
Regarding Claim 16, Watts further discloses the method of claim 1, wherein controlling the arm and/or the end effector to move without colliding with the ceiling of the container comprises:
determining a trajectory of the arm of the mobile robot based, at least in part, on the estimate of the geometry of the ceiling of the container (See Fig. 2A and Col. 10 as referenced above); and
moving the arm in accordance with the trajectory (See Fig. 2A and Col. 10 as referenced above).
Regarding Claim 17, Watts further discloses the method of claim 1, wherein controlling the arm and/or the end effector to move without colliding with the ceiling of the container comprises:
determining a grasp strategy for grasping an object in the container based, at least in part, on the estimate of the geometry of the ceiling of the container (See Col. 11 as referenced above, as well as Lines 41-58, “[…] positioned within an environment such as a warehouse environment and used to pick up, move, and/or otherwise manipulate objects within reach […] may include a robotic arm 222 with an end-effector-mounted gripper 224, which may be of the same type as the robotic manipulator 202 and gripper 204 described with respect to the robotic truck unloader 200. The robotic arm 222 may be mounted on a pedestal 226, which may allow the robotic arm 222 to easily pick up and move nearby packages, such as to distribute packages between different mobile robots […] may include an actuator to allow a control system to change the height of the robotic arm 222.” Examiner notes manipulating the robot arm with the attached gripper to appropriately grasp an object is a grasp strategy, which uses the distance measurements gathered from the sensors when localizing the robot in the environment); and
grasping the object using the grasp strategy (See Col. 11 as referenced above).
Regarding Claim 19, Watts further discloses the method of claim 1, wherein the end effector comprises a suction-based gripper (See Col. 11 Lines 19-23, “[…] the robotic arm 202 may be equipped with a gripper 204, such as a digital suction grid gripper. In such embodiments, the gripper may include one or more suction valves […]”).
Regarding Claim 20, Watts further discloses a mobile robot, comprising:
a mobile base (See Fig. 2A above and Col. 10 Lines 51-52, “[…] planning collision-free trajectories for the one or more robotic arms and/or a mobile base.”);
an arm coupled to the mobile base (See Fig. 2A and Col. 10 Lines 51-52 as referenced above);
a gripper coupled to the arm, wherein the gripper includes one or more distance sensors arranged thereon (See Col. 10 Lines 53-55, “[…] may include a robotic arm 202 with a gripping component 204 for gripping objects […]” See also Col. 10 Line 67 to Col. 11 Lines 1-4, “[…] may use one or more sensors attached to a robotic arm 202, such as sensor 206 and sensor 208, which may be two-dimensional (2D) sensors and/or 3D depth sensors […]”); and
a controller configured to:
determine an estimate of a geometry of a ceiling of a container within which the mobile robot is configured to operate based on distance measurement data sensed by the one or more distance sensors (See Col. 4 Lines 55-63 as referenced above. See also Col. 2 Lines 14-36, “[…] when executed by a control system of a robotic device, cause the control system to perform functions.”).
wherein controlling the arm and/or the gripper comprises controlling the arm and/or the gripper to move without colliding with the ceiling of the container (See Col. 10-11 as referenced above).
But does not explicitly disclose the ceiling of the container being within reach of the arm and/or gripper of the mobile robot; and
the controller configured to control the arm and/or the gripper based, at least in part, on the estimate of the geometry of the ceiling of the container.
Criswell, in a similar field of endeavor, teaches the ceiling of the container being within reach of the arm and/or gripper of the mobile robot (See 0051-0052, 0057 and Fig. 1 as referenced above).
Pardi, in a similar field of endeavor, teaches the controller configured to control the arm and/or the gripper based, at least in part, on the estimate of the geometry of the ceiling of the container (See Abstract as referenced above).
In view of Criswell and Pardi’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the mobile robot measuring distances to building surfaces including ceilings and using representations of such surfaces for navigation, localization, and motion planning within a container or building environment as disclosed by Watts, the ability to use the distance measurements to generate and control trajectories of the robot’s arm or end-effector including reachable space near the ceiling, with a reasonable expectation of success, since each robot relies on sensor-derived surface estimates and their combination predictably improves safety and motion planning in confined robotic environments.
Regarding Claim 21, Watts further discloses a component of a mobile robot, the component comprising:
an arm configured to couple to a base of the mobile robot (See Fig. 2A, 4C along with Col. 4, Col. 10 and Col. 11 as referenced above); and
an end effector coupled to the arm, the end effector including one or more distance sensors (See Fig. 2A, 4C along with Col. 4, Col. 10 and Col. 11 as referenced above), wherein
the arm is configured to move through a scan trajectory (See Col. 10 Lines 43-52 and Col. 11 Lines 9-18 as referenced above),
the end effector is configured to orient a first distance sensor of the one or more distance sensors toward a ceiling of a container (See Fig. 4C and Col. 16 Lines 18-20 as referenced above),
the first distance sensor is configured to capture first distance measurements as the arm is moved through the scan trajectory (See Fig. 4C and Col. 16 Lines 18-20 as referenced above), and
an estimate of a geometry of the ceiling of the container is determined based, at least in part, on the first distance measurements (See Col. 4 Lines 55-63 and Col. 13 Lines 35-57 as referenced above), and
the arm and/or the end effector is controlled to move without colliding with the ceiling of the container (See Col. 10-11 as referenced above).
But does not explicitly disclose the ceiling of the container being within reach of the arm and/or end effector,
the arm and/or the end effector is controlled to move without colliding with the ceiling of the container based, at least in part, on the estimate of the geometry of the ceiling of the container.
Criswell, in a similar field of endeavor, teaches the ceiling of the container being within reach of the arm and/or end effector (See 0051-0052, 0057 and Fig. 1 as referenced above).
Pardi, in a similar field of endeavor, teaches the arm and/or the end effector is controlled to move without colliding with the ceiling of the container based, at least in part, on the estimate of the geometry of the ceiling of the container (See Abstract as referenced above).
In view of Criswell and Pardi’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the mobile robot measuring distances to building surfaces including ceilings and using representations of such surfaces for navigation, localization, and motion planning within a container or building environment as disclosed by Watts, the ability to use the distance measurements to generate and control trajectories of the robot’s arm or end-effector including reachable space near the ceiling, with a reasonable expectation of success, since each robot relies on sensor-derived surface estimates and their combination predictably improves safety and motion planning in confined robotic environments.
Claim 7 is rejected under 35 U.S.C. 103 as being obvious over Watts (US Patent No. 9,632,504 B1) in view of Criswell (US Patent Pub. No. 2019/0315582 A1) and Pardi et al. (“Maximally Manipulable Vision-Based Motion Planning for Robotic Rough-Cutting on Arbitrarily Shaped Surfaces”) as applied to claim 1 above, and further in view of Cheah et al. (“MIRRAX: A Reconfigurable Robot for Limited Access Environments”).
Regarding Claim 7, Watts in view of Criswell and Pardi teaches the method of claim 1, but does not explicitly teach wherein sensing distance measurement data is performed while a base of the mobile robot is outside of the container.
Cheah, in a similar field of endeavor, teaches sensing distance measurement data is performed while a base of the mobile robot is outside of the container (See Abstract, “[…] conventional mobile robots are unable to address the challenge of operating in extreme environments where the robot is required to traverse narrow gaps in highly cluttered areas with restricted access […] a robot designed to meet these challenges by way of its reconfigurable capability.” See also Pg. 1341, “[…] navigating through constrained and cluttered areas, and another is that access points may be restricted […]” Examiner emphasizes the design and control of this robot for approaching and entering narrow or restricted environments for inspection and mapping, demonstrating a conventional robotics strategy of approaching a confined space from outside and planning entry before physically entering).
In view of Cheah’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with the mobile robot measuring distances to building surfaces including ceilings and using representations of such surfaces for navigation, localization, and motion planning of both the robot and it’s end effector within a container or building environment as disclosed by Watts in view of Criswell and Pardi, the ability to perform sensing while the robot base is outside the container, with a reasonable expectation of success, since it is common practice in mobile robotics to perceive and approach cluttered or restricted access environments prior to and during operation. The stated need to traverse narrow gaps and restricted environments for the MIRRAX robot shows that environment sensing and mapping must occur as the robot approaches these regions, thus supporting the performance of distance measurements while the base remains outside prior to full entry. Therefore, combining this common robotics practice with a mobile robot already capable of distance sensing and ceiling estimation would have been obvious to allow sensing while the robot base remains outside the container for improved planning and control.
Claims 9-11 are rejected under 35 U.S.C. 103 as being obvious over Watts (US Patent No. 9,632,504 B1) in view of Criswell (US Patent Pub. No. 2019/0315582 A1) and Pardi et al. (“Maximally Manipulable Vision-Based Motion Planning for Robotic Rough-Cutting on Arbitrarily Shaped Surfaces”) as applied to claims 1 and 8 above, and further in view of Gutmann et al. (EP Patent Pub. No. 2 776 216 B1), herein “Gutmann”.
Regarding Claim 9, Watts in view of Criswell and Pardi teaches the method of claim 8, but does not explicitly teach wherein determining an estimate of a geometry of the ceiling of the container based on the distance measurement data further comprises:
determining the at least one datum as a datum having a minimum distance in the distance measurement data.
Gutmann, in a similar field of endeavor, teaches determining an estimate of a geometry of the ceiling of the container based on the distance measurement data (See 0011, “[…] indoor navigation which employs active beacons in the form of navigation cubes that project two patterns onto the ceiling in the area […]”) further comprises:
determining the at least one datum as a datum having a minimum distance in the distance measurement data (See 0247, “[…] after traveling a certain minimum distance and integrating a certain minimum number of measurements, it can be concluded that the tracking filter succeeded. The process can then switch back to Vector Field SLAM […]” See also 0279, “[…] a required minimum tracking distance also enforces an adequate minimum number of readings.”).
In view of Gutmann’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with method of estimating a ceiling location using sensors attached to a robot arm as disclosed by Watts, the distance measurement data to include having a minimum distance, with a reasonable expectation of success, since the invention in Watts involves analyzing variations in detected distances to the ceiling at different points of measurement to determine contour outlines, so the system is already capable of measuring and comparing different distances to determine a minimum value, and it has been held that where the general conditions of a claim are disclosed in the prior art, discovering the working ranges involves only routine skill in the art.
Regarding Claim 10, Watts further discloses the method of claim 8, wherein determining an estimate of a geometry of the ceiling of the container based on the distance measurement data further comprises:
determining the estimate of the geometry of the ceiling of the container based on the filtered distance measurement data (See Col. 4 Lines 55-63 as referenced above).
But does not explicitly disclose filtering the distance measurement data to generate filtered distance measurement data.
Gutmann, in a similar field of endeavor, teaches filtering the distance measurement data to generate filtered distance measurement data (See 0247-0248, “[…] after traveling a certain minimum distance and integrating a certain minimum number of measurements, it can be concluded that the tracking filter succeeded […] the tracking filter ignores to covariances associated with the nodes in the map […] used over a short distance of robot travel and only to verify our pose hypothesis. Thus, the consistency of this filter is not a primary concern. A property of the filter is that we only need to maintain the robot pose […]”).
In view of Gutmann’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with method of estimating a ceiling location using sensors attached to a robot arm as disclosed by Watts, the distance measurement data to include having filtered distance data, with a reasonable expectation of success, since the invention in Watts involves analyzing variations in detected distances to the ceiling at different points of measurement to determine contour outlines, so the system is already capable of measuring and comparing different distances to determine variations, and implementing a filter for statistical outliers in the gathered measurements improves the accuracy of the data over longer times and distances of operation.
Regarding Claim 11, Watts in view of Criswell and Pardi does not explicitly teach the method of claim 10, wherein filtering the distance measurement data comprises:
sorting the distance measurement data in order of distance to generate sorted data; and
excluding from the filtered distance measurement data, a threshold amount of the sorted data with the smallest distances.
Gutmann, in a similar field of endeavor, teaches filtering the distance measurement data comprises:
sorting the distance measurement data in order of distance to generate sorted data (See 0095, “[…] initial sequence typically contains a minimum or relatively low number of sensor samples (e.g., 2 to 50) while the mobile device 100 moves a certain distance. This distance is usually proportional to the chosen cell size such that enough samples are available that cover a reasonable fraction of the cell […] for a cell size of 1 meter, the distance threshold may be selected within the range of 0.5 m to 1 meter. More generally, some embodiments may be configured to travel a distance of 1/3 to 2/3 of the cell size.”); and
excluding from the filtered distance measurement data, a threshold amount of the sorted data with a smallest distances (See 0245, “[…] distance falls above a threshold, i.e. D ( z t ) > Dmax, then the measurement z t is rejected. A typical threshold is D max = 3. Otherwise, the measurement z t is accepted, and the robot pose is updated […]”).
In view of Gutmann’s teachings, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to include, with method of estimating a ceiling location using sensors attached to a robot arm as disclosed by Watts, the distance measurement data to be sorted and exclude a certain threshold of distances, with a reasonable expectation of success, since the invention in Watts involves analyzing variations in detected distances to the ceiling at different points of measurement to determine contour outlines, so the system is already capable of measuring and comparing different distances to determine variations, and excluding a threshold of distances can improve the operational efficiency of generating the depth map by eliminating irrelevant or outlying distance measurements that would not affect the robot’s function.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bryant Tang whose telephone number is (571)270-0145. The examiner can normally be reached M-F 8-5 PST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Worden can be reached at (571)272-4876. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BRYANT TANG/Examiner, Art Unit 3658
/THOMAS E WORDEN/Supervisory Patent Examiner, Art Unit 3658
