DETAILED ACTION
Introduction
Claims 1-20 have been examined in this application. Claims 1, 2, 4, 6-14, 19, and 20 are amended. Claims 3 and 5 are as previously presented. Claims 15-18 are original.
This is a non-final office action in response to the Request for Continued Examination filed 7/8/2026. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Office Action Formatting
The following is an explanation of the formatting used in the instant Office Action:
• [0001] – Indicates a paragraph number in the most recent, previously cited source;
• [0001, 0010] – Indicates multiple paragraphs (in example: paragraphs 1 and 10) in the most recent, previously cited source;
• [0001-0010] – Indicates a range of paragraphs (in example: paragraphs 1 through 10) in the most recent, previously cited source;
• 1:1 – Indicates a column number and a line number (in example: column 1, line 1) in the most recent, previously cited source;
• 1:1, 2:1 – Indicates multiple column and line numbers (in example, column 1, line 1 and column 2, line 2) in the most recent, previously cited source;
• 1:1-10 – Indicates a range of lines within one column (in example: all lines spanning, and including, lines 1 and 10 in column 1) in the most recent, previously cited source;
• 1:1-2:1 – Indicates a range of lines spanning several columns (in example: column 1, line 1 to column 2, line 1 and including all intervening lines) in the most recent, previously cited source;
• p. 1, ln. 1 – Indicates a page and line number in the most recent, previously cited source;
• ¶1 – The paragraph symbol is used solely to refer to Applicant's own specification (further example: p. 1, ¶1 indicates first paragraph of page 1); and
• BRI – the broadest reasonable interpretation.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/8/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDS is being considered by the examiner.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 7/8/2026 has been entered.
Response to Arguments
Applicant's arguments, filed 7/8/2026, have been fully considered.
Regarding the arguments pertaining to the claim rejections under 112 (presented on p. 8), the arguments and amendments are persuasive. Therefore, the rejections have been withdrawn.
Regarding the remarks pertaining to the claim interpretation under 112(f) (presented on p. 9), the remarks are acknowledged and based on the amendments, no terms in the claims are presently interpreted as invoking 112(f).
Regarding the arguments pertaining to the claim rejections under 103 (presented on p. 1), the arguments and amendments are persuasive. Therefore, the rejections have been withdrawn. However, upon further consideration, a new grounds of rejection is made in view of the additional prior art of Published Application US2021/0341940A1 (Baik) as well as the previously relied upon prior art of NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al.), Publication JP2015080832A (Ogawa), Published Application US2021/0114620A1 (Yu et al.), Patent U.S. 11,274,930 B1 (Madhivanan et al.), Publication US2018/0111261A1 (Asada et al.), and NPL Publication “Real-time step edge estimation using stereo images for biped robot” (Asatani et al.).
Claim Objections
Claim 1 is objected to because of the following informalities:
In Claim 1, “receiving, at least one processor of a legged robot” should instead read “receiving, by at least one processor of a legged robot”
Appropriate correction is required.
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 use the word “means” or “step” but are nonetheless not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph because the claim limitation(s) recite(s) sufficient structure, materials, or acts to entirely perform the recited function. Such claim limitations are:
(a) the recitation of “step” in the Claims 1, 16, 17, 19, and 20.
Examiner’s note: the term “step” in “no-step region” is not a placeholder for acts and therefore does not invoke 112(f).
Because this/these claim limitation(s) is/are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are not being interpreted to cover only the corresponding structure, material, or acts described in the specification as performing the claimed function, and equivalents thereof.
If applicant intends 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 remove the structure, materials, or acts that performs the claimed function; or (2) present a sufficient showing that the claim limitation(s) does/do not recite sufficient structure, materials, or acts to perform the claimed function.
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, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik).
Regarding Claim 1, Gutmann et al. discloses a method comprising:
receiving, at least one processor of a legged robot (see Figure 6, and p. 1069, section IV, humanoid robot with CPUs), from a sensor of the legged robot (see p. 1067 section III. part A, range sensor data, p. 1069 stereo cameras of QRIO robot), sensor data of an environment of the legged robot (see p. 1067 section III. data about environment);
generating, by the at least one processor, a map of at least one of an obstacle or a no-step region within the environment based on the sensor data (see p. 1067 Section III. generating 3D occupancy grid, and see Figure 3(c) and p. 1069 part E., 3D occupancy grid with complete representation of scene including obstacles (which p. 1067 are places the robot cannot step on));
generating, by the at least one processor, a stair model of at least one stair within the environment based on the sensor data (see p. 1068, section III. part C, 2.5D Floor Height map, and see Figure 3(b), including height of stair steps), wherein the stair model disagrees with the map with regard to obstacle existence or no-step region existence for a location in the environment (see p. 1069 part E. “The floor height map captures the precise floor height but cannot represent any obstacles” as opposed to 3D occupancy grid); and
controlling, by the at least one processor, the legged robot to traverse a first portion of the environment using the map (see p. 1068 part D. compute Floor and Obstacle Grid based on both floor and 3D occupancy grid, and see Figure 6, p. 1070 Section V. QRIO robot walk between obstacles. Examiner’s note: merging of the map and stair model and then traversing using the merged model is determined to read on “using” the map. The claim does not specify or require using only the map.) and a second portion of the environment using the stair model that is distinct from the map (see p. 1068 part D. compute Floor and Obstacle Grid based on both floor and 3D occupancy grid, and see Figure 6, p. 1070 Section V. QRIO robot climb up and down sill).
Gutmann et al. does not explicitly recite: wherein subsequent to controlling the legged robot to traverse the first portion of the environment and the second portion of the environment, the at least one processor maintains the map and the stair model.
Examiner’s note: the limitation interpreted, per the arguments filed 7/8/2026, as the map and stair model being stored in an un-merged state.
However, Baik teaches a technique in robot operation (see [0035] autonomous vehicle), using multiple maps/models to represent an environment (see Figure 1 and [0069] map layers):
wherein subsequent to controlling the vehicle to traverse the first portion of the environment and the second portion of the environment (see [0082] subsequent to traveling through first area and second area by using “at least one map layer”), the at least one processor (see [0082] vehicle and server) maintains the first map layer and the second map layer (see [0082] traveling in a third area, by receiving again at least one map layer based on third profile, and see [0062] map layers stored in server, and extracted as needed i.e. maintained separately throughout traveling).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the floor height map and stair models of Gutmann et al. to be maintained and extracted as needed as map layers, as taught by Baik, with a reasonable expectation of success, with the motivation of improving the efficiency and reliability by selectively using the required amount of data (see Baik, [0005-0006]).
Regarding Claim 2, Gutmann et al. discloses the method of claim 1, wherein generating the map comprises:
generating the map using a perception system of the legged robot, wherein the perception system comprises a first processor of the at least one processor and first memory (see p. 1069 Section IV., QRIO robot performing the mapping operations, using CPU(s)),
wherein generating the stair model comprises:
generating the stair model using a stair tracker of the legged robot, wherein the stair tracker comprises a processor (see p. 1069 Section IV., QRIO robot performing the mapping operations, using CPU(s)).
Gutmann et al. further discloses multiple processors (see p. 1069) but does not explicitly recite: wherein the stair tracker comprises a second processor of the at least one processor that is different from the first processor and second memory.
Examiner’s note: in other words, Gutmann et al. does not explicitly recite that the functions of creation of the floor map and occupancy grid are performed by two different processors.
However, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to assign the different tasks of Gutmann et al. to the different processors of Gutmann et al., with a reasonable expectation of success, since there are a finite number of identified, predictable, potential solutions (the functions on the same processor or different processors or distributed across plural processors), and one or ordinary skill in the art would have been motivated to pursue the different solutions in order to optimize the speed and processor load and balancing computing resources (see p. 1070).
Regarding Claim 3, Gutmann et al. discloses the method of claim 1, wherein the map and the stair model comprise different dimensional models of the environment (see p. 1068, 3D occupancy grid and 2.5D floor map).
Regarding Claim 4, Gutmann et al. discloses the method of claim 1, further comprising:
determining to use the map to traverse the first portion of the environment and the stair model to traverse the second portion of the environment based on a mode of the legged robot (see p. 1070, section V., walking/climbing being a traversing type of operation as opposed to mere sensor observation (mode defined as a manner of acting or doing; method; way)).
Regarding Claim 5, Gutmann et al. discloses the method of claim 1, further comprising:
determining to override a portion of the stair model corresponding to the location in the environment with a portion of the map corresponding to the location in the environment (see p. 1068-1069, floor height map (stair model) cannot represent obstacles but combined with 3D occupancy grid to form Floor and Obstacle grid which represents obstacle) based on a mode of the legged robot (see p. 1068 based on operation to compute Floor and Obstacle Grid (mode defined as a manner of acting or doing; method; way)).
Regarding Claim 6, Gutmann et al. discloses the method of claim 1, wherein controlling the legged robot to traverse the second portion of the environment comprises:
controlling the legged robot to traverse the at least one stair using the stair model (see p. 1068 part D. compute Floor and Obstacle Grid using both floor and 3D occupancy grid, and see Figure 6, p. 1070 Section V. QRIO robot climb up and down sill), wherein each of the map and the stair model individually define the at least one stair (see Figure 3(b), 3(c), map and stair model each characterizing stair by floor height or 3D occupancy).
Regarding Claim 8, Gutmann et al. discloses the method of claim 1, wherein the first portion of the environment is identified for traversal using the map (see p. 1068 final step of computing floor and obstacle grid using the 3D occupancy grid, and p. 1070 walk between obstacles) and the second portion of the environment is identified for traversal using the stair model (see p. 1068 final step of computing floor and obstacle grid using the 3D occupancy grid, and p. 1070 climb sill) according to data associated with the legged robot (see p. 1067, 1070, according to the sensor data which is associated with the robot).
Regarding Claim 12, Gutmann et al. discloses the method of claim 1, further comprising:
merging the stair model and the map to generate a merged map (see p. 1068 computing the floor and obstacle grid); and;
controlling the legged robot to traverse a third portion of the environment using the merged map (see p. 1066 final map for navigation is the floor and obstacle grid, and p. 1068-1070, computing floor and obstacle grip as final step before implementing).
Regarding Claim 13, Gutmann et al. discloses the method of claim 1, wherein the map identifies the obstacle, wherein the obstacle comprises a wall of the at least one stair or an obstacle on the at least one stair (see p. 1069, 3D occupancy grid, as shown in Figure 3(c) with portion of obstacle on top stair).
Regarding Claim 14, Gutmann et al. discloses the method further comprising:
merging the stair model and the map to generate a merged map (see p. 1068 computing the floor and obstacle grid),
Gutmann et al. does not explicitly recite the method of claim 1,
wherein controlling the legged robot to traverse the first portion of the environment using the map and the second portion of the environment using the stair model that is distinct from the map is subsequent to merging the stair model and the map.
However, Baik teaches the technique as above,
wherein controlling the vehicle to traverse the first portion of the environment using the first map and the second portion of the environment using the second map that is distinct from the map is subsequent to merging the first and second map (see [0082] for the case of “at least one” layers to navigate the first area being plural layers (i.e. first precise map being merged map) followed by navigation of second and third area using “at least one” layer being for single layer, i.e. only with first map and second map).
The motivation to combine Gutmann et al. and Baik was provided in the rejection of Claim 1.
Regarding Claim 16, Gutmann et al. discloses the method of claim 1, wherein the map identifies the no-step region, wherein the no-step region comprises an area of the environment see p. 1067 Section III. generating 3D occupancy grid, and see Figure 3(c) and p. 1069 part E., 3D occupancy grid with complete representation of scene including obstacles (which p. 1067 are places the robot cannot step on).
Regarding Claim 19, Gutmann et al. discloses a legged robot (see Figure 6, and p. 1069, section IV, humanoid robot) comprising:
a body (see Figure 6, and p. 1069, section IV, humanoid robot);
a sensor coupled to the body (see p. 1067 section III. part A, range sensor data, p. 1069 stereo cameras of QRIO robot);
two or more legs coupled to the body and configured to traverse an environment of the legged robot (see Figures 5, 6, and p. 1069, section IV, humanoid robot); and
a control system comprising a processor and memory hardware in communication with the processor, the memory hardware storing instructions, wherein execution of the instructions by the processor causes the processor to (see p. 1069, section IV, implemented on CPUs):
receive, from the sensor, sensor data of the environment (see p. 1067, 1069 section III. camera data about environment);
generate a map of at least one of an obstacle or a no-step region within the environment based on the sensor data (see p. 1067 Section III. generating 3D occupancy grid, and see Figure 3(c) and p. 1069 part E., 3D occupancy grid with complete representation of scene including obstacles (which p. 1067 are places the robot cannot step on));
generate a stair model of at least one stair within the environment based on the sensor data (see p. 1068, section III. part C, 2.5D Floor Height map, and see Figure 3(b), including height of stair steps), wherein the stair model disagrees with the map with regard to obstacle existence or no-step region existence for a location in the environment (see p. 1069 part E. “The floor height map captures the precise floor height but cannot represent any obstacles” as opposed to 3D occupancy grid); and
control the legged robot to traverse a first portion of the environment using the map (see p. 1068 part D. compute Floor and Obstacle Grid based on both floor and 3D occupancy grid, and see Figure 6, p. 1070 Section V. QRIO robot walk between obstacles. Examiner’s note: merging of the map and stair model and then traversing using the merged model is determined to read on “using” the map. The claim does not specify or require using only the map.) and a second portion of the environment using the stair model that is distinct from the map(see p. 1068 part D. compute Floor and Obstacle Grid based on both floor and 3D occupancy grid, and see Figure 6, p. 1070 Section V. QRIO robot climb up and down sill).
Gutmann et al. does not explicitly recite wherein subsequent to controlling the legged robot to traverse the first portion of the environment and the second portion of the environment, the processor maintains the map and the stair model.
However, Baik teaches a technique in robot operation (see [0035] autonomous vehicle), using multiple maps/models to represent an environment (see Figure 1 and [0069] map layers):
wherein subsequent to controlling the vehicle to traverse the first portion of the environment and the second portion of the environment (see [0082] subsequent to traveling through first area and second area by using “at least one map layer”), the at least one processor (see [0082] vehicle and server) maintains the first map layer and the second map layer (see [0082] traveling in a third area, by receiving again at least one map layer based on third profile, and see [0062] map layers stored in server, and extracted as needed i.e. maintained separately throughout traveling).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the floor height map and stair models of Gutmann et al. to be maintained and extracted as needed as map layers, as taught by Baik, with a reasonable expectation of success, with the motivation of improving the efficiency and reliability by selectively using the required amount of data (see Baik, [0005-0006]).
Regarding Claim 20: the limitations as recited have been analyzed with respect to Claim 1. Therefore, Claim 20 is rejected under the same rationale.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik), further in view of Publication JP2015080832A (Ogawa) (English description relied upon for citations).
Regarding Claim 7, Gutmann et al. does not explicitly recite the method of claim 1, wherein controlling the legged robot to traverse the second portion of the environment is based on activation of a stair mode.
However, Ogawa teaches a legged robot for traversal of environments (see Figures 1, 3, [0007]),
wherein controlling the legged robot to traverse the second portion of the environment is based on activation of a stair mode (see [0033, 0041] change to ascending stair gait generation method).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the robot of Gutmann et al. to have a stair mode as taught by Ogawa, with a reasonable expectation of success, with the motivation of improving stair traversal and interactions in environments with people (see Ogawa, [0005]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik), further in view of Published Application US2021/0114620A1 (Yu et al.).
Regarding Claim 9, Gutmann et al. discloses controlling the legged robot to traverse the first and second portions of the environment (see p. 1070 walk between obstacles and climb up and down sill).
Gutmann et al. does not explicitly recite the method of claim 1, wherein controlling the legged robot to traverse the first portion of the environment comprises controlling the legged robot to traverse the first portion of the environment according to a first manner of obstacle avoidance, and wherein controlling the legged robot to traverse the second portion of the environment comprises controlling the legged robot to traverse the second portion of the environment according to a second manner of obstacle avoidance.
However, Yu et al. teaches a technique of obstacle avoidance, wherein controlling a robot to traverse an environment comprises:
controlling the robot to traverse according to a first manner of obstacle avoidance, and wherein controlling the robot comprises controlling the robot to traverse according to a second manner of obstacle avoidance (see [0053], obstacle without moving characteristics has a move around avoidance, while moving obstacle uses trajectory comparison).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to try the first manner of obstacle avoidance of Yu et al. in the first portion disclosed in Gutmann et al., and second manner of obstacle avoidance of Yu et al. in the second portion, disclosed in Gutmann et al., because there are a finite number of identified, predictable potential solutions (i.e. limited combinations of how to apply two types of obstacle avoidance to two different areas), and one of ordinary skill in the art would have pursued such solutions with a reasonable expectation of success, with the motivation of providing improved adaptability to various obstacles and situations and improving safety (see Yu et al. [0003, 0053]).
Claims 10, 11, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik), further in view of Patent U.S. 11,274,930 B1 (Madhivanan et al.).
Regarding Claim 10, Gutmann et al. discloses the method further comprising:
adding an obstacle to the stair model based on additional sensor data (see p. 1068 computing floor and obstacle grid is adding obstacle information from the 3D occupancy grid to the floor height map (stair model)), wherein the sensor data and the additional sensor data indicate different features within the environment (any second piece of sensor data or use in new environment being “additional” sensor data),
wherein controlling the legged robot to traverse the second portion of the environment comprises controlling the legged robot to traverse the second portion of the environment based on the obstacle (see p. 1068-1070, controlling travel based on merging floor map and 3D grid (having obstacle)).
Gutmann et al. does not explicitly recite the method of claim 1, further comprising:
adding an indicator to the stair model based on additional sensor data,
and the controlling: based on the indicator.
However, Madhivanan et al. teaches a technique of robot navigation using a map and stair model (see Figure 7, step 704 first occupancy map as map and step 708, submap as stair model, per 7:61-8:13, indicative of presence or absence of obstacles 108, which per 5:4-12 may include stair wells), comprising:
adding an indicator to the stair model based on additional sensor data (see 7:61-8:3, submap indicative of plural obstacles and 5:52-62, obstacles can be tagged with type (indicator). I.e. any second obstacle sensed is based on “additional sensor data” relative to a first obstacle),
wherein controlling the robot is: based on the indicator (see (see Figure 7, 33:15-31 step 714 updating occupancy map based on submap from step 708 and 29:66-30:6 updated occupancy map used for autonomous navigation, i.e. based on submap including indicator).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the map of Gutmann et al. to include obstacle indicator data which gets added to the stair model as taught by Madhivanan et al., with a reasonable expectation of success, with the motivation of improving customization and flexibility by allowing for travel around specific obstacles such as fragile items (see Madhivanan et al. 5:50-60).
Regarding Claim 11, Gutmann et al. discloses the method further comprising:
adding an obstacle to the stair model based on the map, (see p. 1068 computing floor and obstacle grid is adding obstacle information from the map (3D occupancy grid) to the floor height map (stair model)),
wherein controlling the legged robot to traverse the second portion of the environment comprises controlling the legged robot to traverse the second portion of the environment based on the obstacle(see p. 1068-1070, controlling travel based on merging floor map and 3D grid (having obstacle)).
Gutmann et al. does not explicitly recite the method of claim 1, further comprising:
adding an indicator to the stair model based on the map,
wherein controlling the legged robot is based on the indicator.
However, Madhivanan et al. teaches the technique as above, comprising:
adding an indicator to the stair model based on the map (see Figure 7, submap being determined at 708 based on map from step 701, and see 7:61-8:3, submap indicative of obstacles and 5:52-62, obstacles can be tagged with type (indicator))
wherein controlling the robot is based on the indicator (see (see Figure 7, 33:15-31 step 714 updating occupancy map based on submap from step 708 and 29:66-30:6 updated occupancy map used for autonomous navigation, i.e. based on submap including indicator).
The motivation to combine Gutmann et al. and Madhivanan et al. was provided in the rejection of Claim 10.
Regarding Claim 15, Gutmann et al. does not explicitly recite the method of claim 1, wherein the map identifies the obstacle, wherein the obstacle comprises an object.
However, Madhivanan et al. teaches the technique as above, comprising:
wherein the map identifies the obstacle, wherein the obstacle comprises an object (see 5:33-48 occupancy map indicates locations of one or more obstacles, 5:36-40, e.g. table).
The motivation to combine Gutmann et al. and Madhivanan et al. was provided in the rejection of Claim 10.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik), further in view of Publication US2018/0111261A1 (Asada et al.).
Regarding Claim 17, Gutmann et al. does not explicitly recite the method of claim 1, wherein the map identifies the no-step region, wherein the no-step region comprises an edge of the at least one stair.
However, Asada et al. teaches a robot for traversal of environments (see Figure 7):
wherein the map identifies the no-step region, wherein the no-step region comprises an edge of the at least one stair (see [0021] edge of a staircase as unsafe place to step).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the robot and control technique of Gutmann et al. to identify edges of stairs as no-step region as taught by Asada et al., with a reasonable expectation of success, with the motivation of improving safety and reliability (see Asada et al., [0021]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over NPL Publication “A Floor and Obstacle Height Map for 3D Navigation of a Humanoid Robot” (Gutmann et al. – on IDS filed with instant application 8/30/2024 and copy in file wrapper of 16/877,749 filed 10/31/2022) in view of Published Application US2021/0341940A1 (Baik), further in view of NPL Publication “Real-time step edge estimation using stereo images for biped robot” (Asatani et al.).
Regarding Claim 18, Gutmann et al. does not explicitly recite the method of claim 1, wherein generating the stair model comprises:
generating a first stair model of the at least one stair corresponding to ascent of the at least one stair; and
generating a second stair model of the at least one stair corresponding to descent of the at least one stair, wherein the stair model comprises the first stair model or the second stair model.
However, Asatani et al. teaches a robot for traversal of environments (see Figure 8, Abstract), wherein generating the stair model comprises:
generating a first stair model of the at least one stair corresponding to ascent of the at least one stair (see p. 4465, Figure 4(b), upward case with riser modeled); and
generating a second stair model of the at least one stair corresponding to descent of the at least one stair (see p. 4465, Figure 4(a), downward case without riser), wherein the stair model comprises the first stair model or the second stair model (see Section IV, modeling both upward and downward case).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to modify the robot and stair model of Gutmann et al. to have ascent and descent models as taught by Asatani et al., with a reasonable expectation of success, with the motivation of further improving stair navigation (see Asatani et al., Abstract).
Conclusion
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/P.A./Examiner, Art Unit 3669
/Erin M Piateski/Supervisory Patent Examiner, Art Unit 3669
