DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first
inventor to file provisions of the AIA .
Status of Claims
This is the first Office action on the merits. Claims 1-14 are currently pending and addressed below.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“fixed object-based map generating part” provided in claim 1
“first moving object-based map generating part” provided in claim 1
“second moving object-based map generating part” provided in claim 1
“autonomous driving providing part” provided in claim 1
“integrated map generating part” provided in claim 10
The specification and drawings were used to define the generic placeholder specified above (items a-e):
Specification – The corresponding structure or material as performing the claimed functions in items listed above are not disclosed in the specification.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-14 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites claim limitations “fixed object-based map generating part”, “first moving object-based map generating part”, “second moving object-based map generating part”, and “autonomous driving providing part”. Further descriptions for fixed object-based map generating part, first moving object-based map generating part, second moving object-based map generating part, and autonomous driving providing part are not provided for these limits beyond their general terms. Therefore, it is not made clear to one in the ordinary skill in that art and not properly described in the specification of what the fixed object-based map generating part, first moving object-based map generating part, second moving object-based map generating part, and autonomous driving providing part are in terms of structure, material, or apparatus to be linked to the claim’s functions.
Claims 2-9 are rejected by virtue of dependency on claim 1.
Claim 10 recites claim limitation “integrated map generating part”. Further descriptions for integrated map generating part are not provided for these limits beyond their general terms. Therefore, it is not made clear to one in the ordinary skill in that art and not properly described in the specification of what the integrated map generating part is in terms of structure, material, or apparatus to be linked to the claim’s functions.
Claims 11-14 are rejected by virtue of dependency on claim 10.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-14 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites limitations “fixed object-based map generating part”, “first moving object-based map generating part”, “second moving object-based map generating part”, and “autonomous driving providing part” which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed associated functions and to clearly link the structure, material, or acts to the associated functions. The written description does not describe or further define “fixed object-based map generating part”, “first moving object-based map generating part”, “second moving object-based map generating part”, and “autonomous driving providing part” beyond these general terms so there is insufficient disclosure of the corresponding structure and material and the written description does not link a defined structure or material to the claimed functions. Therefore, independent claim 1 is indefinite and rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Claims 2-9 are rejected by virtue of dependency on claim 1.
Claim 10 recites limitation “integrated map generating part” which invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed associated functions and to clearly link the structure, material, or acts to the associated functions. The written description does not describe or further define “integrated map generating part” beyond these general terms so there is insufficient disclosure of the corresponding structure and material and the written description does not link a defined structure or material to the claimed functions. Therefore, independent claim 10 is indefinite and rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Claims 11-14 are rejected by virtue of dependency on claim 10.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process without significantly more.
101 Analysis – Step 1
Claims 1 and 10 are directed to an autonomous driving map generation device (i.e., a machine). Therefore, claims 1 and 10 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claims 1 and 10 include limitations that recite an abstract idea and will be used as a representative claim for the remainder of the 101 rejection.
Independent claims 1 and 10 recite the following information:
An autonomous driving map generation device comprising:
a fixed object-based map generating part that generates a first high-precision map for autonomous driving on the basis of a fixed position corresponding to a fixed object;
a first moving object-based map generating part that recognizes a fixed object marker corresponding to the fixed object on the basis of a first moving object LiDAR provided in a first moving object to generate a second high-precision map for autonomous driving;
a second moving object-based map generating part that recognizes a first moving object marker corresponding to the first moving object on the basis of a second moving object LiDAR provided in a second moving object to generate a third high-precision map for autonomous driving; and
an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving, and transmits the third high-precision map to the second moving object for autonomous driving.
The examiner submits that the foregoing bolded limitation(s) constitute an abstract idea of a mental process that gathers information obtained by observation and sensors related to the position of objects in an autonomous vehicle system environment, and develops maps based on the position of objects observed in the environment.
Each of the limitations can be performed in the mental realm or by using pen and paper to gather information based on visual observation of displayed features for objects in an environment captured by LiDAR sensors and generate a map of the environment based on the gathered information for the objects in the environment.
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. It must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
Claims 1 and 10 do contain additional elements of an autonomous driving map generation device, a fixed object-based map generating part, a first moving object-based map generating part, a first moving object LiDAR provided in a first moving object, a second moving object-based map generating part, a second moving object LiDAR provided in a second moving object, and an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving, and transmits the third high-precision map to the second moving object for autonomous driving. However, these additional elements do not add to significantly more than the abstract idea of a mental process.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional elements of an autonomous driving map generation device, a fixed object-based map generating part, a first moving object-based map generating part, a first moving object LiDAR provided in a first moving object, a second moving object-based map generating part, a second moving object LiDAR provided in a second moving object, and an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving, and transmits the third high-precision map to the second moving object for autonomous driving, the examiner submits that these limitations merely describe how to generally apply the otherwise mental judgements in a generic or general-purpose autonomous vehicle map generating system environment. The autonomous driving map generation device, a fixed object-based map generating part, a first moving object-based map generating part, a first moving object LiDAR provided in a first moving object, a second moving object-based map generating part, a second moving object LiDAR provided in a second moving object, and an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving, and transmits the third high-precision map to the second moving object for autonomous driving are recited at a high level of generality and merely automate the map generating, object recognizing, and map transmitting components of the system. The examiner submits that these limitations are recited at a high level of generality (i.e., describe general means of the map generating, object recognizing, and map transmitting steps) and therefore amount to mere transmission of data between computer processing components which is a form of insignificant extra-solution activity that merely uses computing components to perform the process.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B, representative independent claims 1 and 10 do not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of an autonomous driving map generation device, a fixed object-based map generating part, a first moving object-based map generating part, a first moving object LiDAR provided in a first moving object, a second moving object-based map generating part, a second moving object LiDAR provided in a second moving object, and an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving, and transmits the third high-precision map to the second moving object for autonomous driving amount to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations of map generating and map transmitting, the examiner submits that these limitations are insignificant extra-solution activities.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field. The additional limitations of gathering/transmitting data are well-understood, routine, and conventional activities because the specification does not provide any indication that the computer is anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Hence, the claims are not patent eligible.
Dependent claims 2-9 and 11-14 do not recite and further limitations that cause the claims to be patent eligible. The limitations of the dependent claims are directed towards additional aspects of the judicial exception that do not integrate the judicial exception into a practical application. The dependent claims further narrow the scope of independent claims 1 and 10, however, the identified additional limitations and elements still do not impose any meaningful limits on practicing the identified abstract ideas. Therefore, dependent claims 2-9 and 11-14 are not patent eligible under the same rationale as provided for in the rejection of claims 1 and 10. Therefore, claims 1-14 are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2, 4-5, 8-11, and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Wong KR 101589943 B1 (“Wong”) in view of Lee KR 102256541 B1 (“Lee”) and Du et al. US 20190052842 A1 (“Du”).
For claim 1, Wong discloses an autonomous driving map generation device (See at least page 1 of Wong – “… method and apparatus for sharing map data between industrial vehicles in a physical environment … Combining feature information associated with local map data to generate global map data for a physical environment; And manipulating one of the plurality of industrial vehicles using at least a part of the global map data… Embodiments of the present invention generally relate to environment-based navigation systems for automated industrial vehicles, and more particularly to methods and apparatus for sharing map data associated with automated industrial vehicles…”) comprising:
a fixed object-based map generating part that generates a map for autonomous driving on the basis of a fixed position corresponding to a fixed object (See at least pages 3-4 – “… the physical environment 100 includes a vehicle 102 coupled to a sensor array 108 as well as a mobile computer 104, a central computer 106, and the like. The sensor array 108 may analyze various objects within the physical environment 100 and may provide data (e.g., image data, video data, etc.) to the mobile computer 104… physical environment 100 also includes a plurality of markers 116… the plurality of markers 116 are beacons that enable environmental based navigation… mobile computer 104 extracts environmental features and determines an accurate, current vehicle pose…” and page 13 of Wong – “… method 600 processes new features for landmark information associated with one or more industrial vehicles … patterns to be matched are selected from the geometric structures of known entities in the environment, such as pallets, loads, and so on… Landmarks represent the physical attributes of the environment that can be used for steering. The method 600 adds new landmarks to the map data …”);
a first moving object-based map generating part that recognizes a fixed object marker corresponding to the fixed object on the basis of a first moving object sensor provided in a first moving object to generate a second map for autonomous driving (See at least page 5 of Wong – “… the present invention utilize and update map information … The local map defines the features in the environment 100 that include features from the area of the environment 100 … the data added to the local map is also stored in the global map so that local map information updated by one vehicle is shared with other vehicles 102 It is used to update the map…”); and
an autonomous driving providing part that transmits the second map to the first moving object for autonomous driving (See at least page 5 of Wong – “… the present invention utilize and update map information … The local map defines the features in the environment 100 that include features from the area of the environment 100 … the data added to the local map is also stored in the global map so that local map information updated by one vehicle is shared with other vehicles 102 It is used to update the map…”).
Wong fails to specifically disclose a fixed object-based map generating part that generates a first high-precision map for autonomous driving on the basis of a fixed position corresponding to a fixed object;
a first moving object-based map generating part that recognizes a fixed object marker corresponding to the fixed object on the basis of a first moving object LiDAR provided in a first moving object to generate a second high-precision map for autonomous driving; and
an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving.
However, Lee, in the same field of endeavor teaches a fixed object-based map generating part that generates a first high-precision map for autonomous driving on the basis of a fixed position corresponding to a fixed object (See at least the Abstract of Lee – “… the method for providing autonomous driving information comprises the steps of: allowing a control server including a lidar sensor to receive high-precision map-related information from a plurality of smart poles installed at a fixed geographic location; allowing the control server to produce an HD map through the high-precision map-related information; and allowing the control server to transmit the produced HD map to a plurality of autonomous vehicles…”);
a first moving object-based map generating part that recognizes a fixed object marker corresponding to the fixed object on the basis of a first moving object LiDAR provided in a first moving object to generate a second high-precision map for autonomous driving (See at least pages 17-18 of Lee – “… the control server may receive a high-precision map A for a corresponding area from an autonomous vehicle and compare the high-precision map B generated by the control server with the high-precision map A… the accuracy of the map A may be high based on the lidar sensor of the autonomous vehicle…”); and
an autonomous driving providing part that transmits the second high-precision map to the first moving object for autonomous driving (See at least pages 17-18 of Lee – “… if there is a sudden construction in a specific area, the map A of the autonomous vehicle may be more accurate… the autonomous driving vehicle uses the sensing information it has acquired…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on an autonomous vehicle to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of a fixed object-based map generating part that generates a first high-precision map for autonomous driving on the basis of a fixed position corresponding to a fixed object as taught by Lee, with a reasonable expectation of success, in order to compare high precision maps and determine which map to use for autonomous driving as specified in at least pages 17-18 of Lee.
Furthermore, Wong also fails to specifically disclose a second moving object-based map generating part that recognizes a first moving object marker corresponding to the first moving object on the basis of a second moving object LiDAR provided in a second moving object to generate a third high-precision map for autonomous driving; and
an autonomous driving providing part that transmits the third high-precision map to the second moving object for autonomous driving.
However, Du, in the same field of endeavor teaches a second moving object-based map generating part that recognizes a first moving object marker corresponding to the first moving object on the basis of a second moving object LiDAR provided in a second moving object to generate a third high-precision map for autonomous driving (See at least [0055] – “… the first vehicle 510 employing a 360 degree camera detection system when travelling in a congested area will have a clear line of sight to some proximate objects 520, 530, 535, and will have an obstructed view 550 to some other proximate objects 540, 545. The system will use the detected information to generate an obstacle map of the local area… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system. In this fashion…the first vehicle 510 could detect and perceive the vehicle 540, 545, which is in an obstructed view 550 to first vehicle 510…” and [0066] of Du – “… system of an individual autonomous … vehicle may superimpose a first set of the detected road users through ego-sensors, such as camera sensors or Lidar… together with a second set of the detected road users by receiving V2X communications …”); and
an autonomous driving providing part that transmits the third high-precision map to the second moving object for autonomous driving (See at least [0055] of Du – “… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Du teaches an autonomous driving system for vehicles that is able to detect other moving vehicles in an obstructed area of a vehicle and generate an obstacle map to transmit to the vehicle so that vehicle is aware of the other moving vehicles in the obstructed area.
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 autonomous driving map generation device as disclosed in Wong to include the feature of an autonomous driving providing part that transmits the third high-precision map to the second moving object for autonomous driving as taught by Du, with a reasonable expectation of success, in order to provide an updated obstacle map to a moving vehicle with an obstructed view so that the vehicle can perceive the obstacles in the obstructed areas as specified in at least [0055] of Du.
For claim 2, Wong discloses wherein the fixed object-based map generating part additionally reflects the fixed position corresponding to the fixed object located in a terminal per yard to generate the first high-precision map for autonomous driving (See at least pages 3-13 – “… the physical environment 100 includes a vehicle 102 coupled to a sensor array 108 as well as a mobile computer 104, a central computer 106, and the like. The sensor array 108 may analyze various objects within the physical environment 100 and may provide data (e.g., image data, video data, etc.) to the mobile computer 104… physical environment 100 also includes a plurality of markers 116… the plurality of markers 116 are beacons that enable environmental based navigation… mobile computer 104 extracts environmental features and determines an accurate, current vehicle pose… mobile computer 104 provides accurate position estimates for the industrial vehicle and updates the local map data 310 with information associated with environmental features… method 600 processes new features for landmark information associated with one or more industrial vehicles … patterns to be matched are selected from the geometric structures of known entities in the environment, such as pallets, loads, and so on… Landmarks represent the physical attributes of the environment that can be used for steering. The method 600 adds new landmarks to the map data … global map module 328 defines global map data 334 as a vector of known landmarks, which can be used to construct a vector of known features … one or more landmark locations are converted to locations in the common coordinate system… the method may generate a request to update the local map to add new features observed by other industrial vehicles…”).
For claim 4, Wong fails to specifically disclose wherein the first moving object-based map generating part recognizes the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR and additionally reflects the positions of the plurality of first moving objects based on the plurality of first moving object markers in the first high-precision map to generate the second high-precision map for autonomous driving.
However, Lee, in the same field of endeavor teaches wherein the first moving object-based map generating part recognizes the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR and additionally reflects the positions of the plurality of first moving objects based on the plurality of first moving object markers in the first high-precision map to generate the second high-precision map for autonomous driving (See at least page 16 of Lee – “…a current position of an object, a moving direction, and a moving speed may be obtained… each of the autonomous vehicles 1621-1, 1620-2, 1620-3, and 1620-4 may also generate information on surrounding objects… the control server may display information on an object in the HD Map based on information acquired from sensors of a plurality of autonomous vehicles or smart poles. That is, the control server can provide information on objects that change in real time along with the HD Map to the autonomous vehicle, and through this, the autonomous driving can be controlled…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on autonomous vehicles to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of the first moving object-based map generating part recognizing the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR as taught by Lee, with a reasonable expectation of success, in order to provide information on objects that change in real time along with the HD Map to the autonomous vehicle as specified in at least page 16 of Lee.
For claim 5, Wong fails to specifically disclose wherein the second moving object-based map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR and additionally reflects the positions of the plurality of second moving objects based on the plurality of second moving object markers in the second high-precision map to generate the third high-precision map for autonomous driving.
However, Du, in the same field of endeavor teaches wherein the second moving object-based map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR and additionally reflects the positions of the plurality of second moving objects based on the plurality of second moving object markers in the second high-precision map to generate the third high-precision map for autonomous driving (See at least [0055] – “… the first vehicle 510 employing a 360 degree camera detection system when travelling in a congested area will have a clear line of sight to some proximate objects 520, 530, 535, and will have an obstructed view 550 to some other proximate objects 540, 545. The system will use the detected information to generate an obstacle map of the local area… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system. In this fashion…the first vehicle 510 could detect and perceive the vehicle 540, 545, which is in an obstructed view 550 to first vehicle 510…” and [0066] of Du – “… system of an individual autonomous … vehicle may superimpose a first set of the detected road users through ego-sensors, such as camera sensors or Lidar… together with a second set of the detected road users by receiving V2X communications …”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Du teaches an autonomous driving system for vehicles that is able to detect other moving vehicles in an obstructed area of a vehicle and generate an obstacle map to transmit to the vehicle so that vehicle is aware of the other moving vehicles in the obstructed area.
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 autonomous driving map generation device as disclosed in Wong to include the feature of the second moving object-based map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR as taught by Du, with a reasonable expectation of success, in order to provide an updated obstacle map to a moving vehicle with an obstructed view so that the vehicle can perceive the obstacles in the obstructed areas as specified in at least [0055] of Du.
For claim 8, Wong discloses wherein the second moving object includes a yard truck, an external truck, or a reach stacker that performs autonomous driving with cargo blocks loaded thereon (See at least page 4 of Wong – “… , the vehicle 102 may be an unmanned transporter, such as an automated forklift, configured to handle / handle or move a plurality of units 114 around the floor 110 an automated guided vehicle…”) and moves at a speed greater than a predetermined second speed in a terminal (See at least page 12 of Wong – “… Sensor data correction 502 utilizes vehicle motion data obtained from various sensor data and then modifies sensor data that may be affected by vehicle motion before this data is transmitted to interface 504… sensor data correction 502 uses wheel diameter and encoder data to calculate speed measurements….”), includes the second moving object marker having a relative position value and moving at the predetermined second speed, and includes a second moving object LiDAR that recognizes the fixed object marker, the first moving object marker, and the second moving object marker (See at least page 15 of Wong – “… Through the use of a global map that is updated using local map data generated by various vehicles, the vehicles can enhance the environment to add steering landmarks and use, for example, as landmarks to enhance steering , And then share the feature information with other vehicles through the global map. In other embodiments, the obstacles become dynamic feature entries in the local map data such that the knowledge of the obstacle is shared by the vehicles via the global map. To improve the use of features, some embodiments may "pre-down" certain types of features, i.e., static features that are repeatedly identified by vehicles may form permanent landmarks in the global map On the other hand, dynamic features newly appearing in the global map may be assigned a pre-down value when the dynamic features are removed from the global map, unless they are updated through another vehicle being observed…”).
For claim 9, Wong fails to specifically disclose wherein the second moving object receives a third high-precision map, and compares, in a case where there are three or more fixed object markers and first moving object markers recognized using the second moving LiDAR, the three or more fixed object markers and first moving object markers with the third high-precision map to measure its own position for autonomous driving.
However, Lee, in the same field of endeavor teaches wherein the second moving object receives a third high-precision map, and compares, in a case where there are three or more fixed object markers and first moving object markers recognized using the second moving LiDAR, the three or more fixed object markers and first moving object markers with the third high-precision map to measure its own position for autonomous driving (See at least pages 17-18 of Lee – “… the autonomous vehicle can determine whether to provide HD Map information in consideration of the sensing accuracy based on the current state of the vehicle and the surrounding environment… the control server may receive a high-precision map A for a corresponding area from an autonomous vehicle and compare the high-precision map B generated by the control server with the high-precision map A. In this case, the control server may provide information on the matching rate (similarity) of the two maps to the vehicle. Here, the accuracy of the map B generated from the data acquired by the control server over a long period of time may be high, but the accuracy of the map A may be high based on the lidar sensor of the autonomous vehicle. As a more specific example, if there is a sudden construction in a specific area, the map A of the autonomous vehicle may be more accurate than the map B of the control server, and in this case, the autonomous driving vehicle uses the sensing information it has acquired…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on autonomous vehicles to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of comparing fixed object markers and first moving object markers with the third high-precision map to measure its own position for autonomous driving as taught by Lee, with a reasonable expectation of success, in order to determine which map to use for autonomous driving as specified in at least pages 17-18 of Lee.
For claim 10, Wong discloses an autonomous driving map generation device (See at least page 1 of Wong – “… method and apparatus for sharing map data between industrial vehicles in a physical environment … Combining feature information associated with local map data to generate global map data for a physical environment; And manipulating one of the plurality of industrial vehicles using at least a part of the global map data… Embodiments of the present invention generally relate to environment-based navigation systems for automated industrial vehicles, and more particularly to methods and apparatus for sharing map data associated with automated industrial vehicles…”) comprising:
an integrated map generating part that reflects a fixed position corresponding to a fixed object, reflects a position of the fixed object based on a fixed object marker corresponding to the fixed object recognized on the basis of a first moving object sensor provided in a first moving object, reflects a position of the first moving object based on a first moving object marker recognized on the basis of a second moving object sensor provided in a second moving object, in a map for autonomous driving (See at least pages 3-13 – “… the physical environment 100 includes a vehicle 102 coupled to a sensor array 108 as well as a mobile computer 104, a central computer 106, and the like. The sensor array 108 may analyze various objects within the physical environment 100 and may provide data (e.g., image data, video data, etc.) to the mobile computer 104… physical environment 100 also includes a plurality of markers 116… the plurality of markers 116 are beacons that enable environmental based navigation… mobile computer 104 extracts environmental features and determines an accurate, current vehicle pose… mobile computer 104 provides accurate position estimates for the industrial vehicle and updates the local map data 310 with information associated with environmental features… method 600 processes new features for landmark information associated with one or more industrial vehicles … patterns to be matched are selected from the geometric structures of known entities in the environment, such as pallets, loads, and so on… Landmarks represent the physical attributes of the environment that can be used for steering. The method 600 adds new landmarks to the map data … global map module 328 defines global map data 334 as a vector of known landmarks, which can be used to construct a vector of known features. The features correspond to features expected to be extracted from the vehicle sensors… industrial vehicles may reference different coordinate systems of the local map data 310. As such, one or more landmark locations are converted to locations in the common coordinate system… the method may generate a request to update the local map to add new features observed by other industrial vehicles…”); and
an autonomous driving providing part that transmits the map to the first moving object and the second moving object for autonomous driving (See at least page 5 of Wong – “… the present invention utilize and update map information … The local map defines the features in the environment 100 that include features from the area of the environment 100 … the data added to the local map is also stored in the global map so that local map information updated by one vehicle is shared with other vehicles 102 It is used to update the map…”).
Wong fails to specifically disclose an integrated map generating part that reflects a position of the fixed object based on a fixed object marker corresponding to the fixed object recognized on the basis of a first moving object LiDAR provided in a first moving object, in an integrated high-precision map for autonomous driving; and
an autonomous driving providing part that transmits the integrated high-precision map to the first moving object for autonomous driving.
However, Lee, in the same field of endeavor teaches an integrated map generating part that reflects a position of the fixed object based on a fixed object marker corresponding to the fixed object recognized on the basis of a first moving object LiDAR provided in a first moving object, in an integrated high-precision map for autonomous driving (See at least the Abstract – “… the method for providing autonomous driving information comprises the steps of: allowing a control server including a lidar sensor to receive high-precision map-related information from a plurality of smart poles installed at a fixed geographic location; allowing the control server to produce an HD map through the high-precision map-related information; and allowing the control server to transmit the produced HD map to a plurality of autonomous vehicles…” and pages 17-18 of Lee – “… the control server may receive a high-precision map A for a corresponding area from an autonomous vehicle and compare the high-precision map B generated by the control server with the high-precision map A… the accuracy of the map A may be high based on the lidar sensor of the autonomous vehicle…”); and
an autonomous driving providing part that transmits the integrated high-precision map to the first moving object for autonomous driving (See at least pages 17-18 of Lee – “… if there is a sudden construction in a specific area, the map A of the autonomous vehicle may be more accurate… the autonomous driving vehicle uses the sensing information it has acquired…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on an autonomous vehicle to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of an integrated map generating part that reflects a position of the fixed object based on a fixed object marker corresponding to the fixed object recognized on the basis of a first moving object LiDAR provided in a first moving object as taught by Lee, with a reasonable expectation of success, in order to compare high precision maps and determine which map to use for autonomous driving as specified in at least pages 17-18 of Lee.
Furthermore, Wong also fails to specifically disclose an integrated map generating part that reflects a position of the first moving object based on a first moving object marker recognized on the basis of a second moving object LiDAR provided in a second moving object, and reflects a position of the second moving object based on a second moving object marker recognized on the basis of the second moving object LiDAR; and
an autonomous driving providing part that transmits the integrated high-precision map to the second moving object for autonomous driving.
However, Du, in the same field of endeavor teaches an integrated map generating part that reflects a position of the first moving object based on a first moving object marker recognized on the basis of a second moving object LiDAR provided in a second moving object, and reflects a position of the second moving object based on a second moving object marker recognized on the basis of the second moving object LiDAR (See at least [0055] – “… the first vehicle 510 employing a 360 degree camera detection system when travelling in a congested area will have a clear line of sight to some proximate objects 520, 530, 535, and will have an obstructed view 550 to some other proximate objects 540, 545. The system will use the detected information to generate an obstacle map of the local area… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system. In this fashion…the first vehicle 510 could detect and perceive the vehicle 540, 545, which is in an obstructed view 550 to first vehicle 510…” and [0066] of Du – “… system of an individual autonomous … vehicle may superimpose a first set of the detected road users through ego-sensors, such as camera sensors or Lidar… together with a second set of the detected road users by receiving V2X communications …”); and
an autonomous driving providing part that transmits the integrated high-precision map to the second moving object for autonomous driving (See at least [0055] of Du – “… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Du teaches an autonomous driving system for vehicles that is able to detect other moving vehicles in an obstructed area of a vehicle and generate an obstacle map to transmit to the vehicle so that vehicle is aware of the other moving vehicles in the obstructed area.
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 autonomous driving map generation device as disclosed in Wong to include the feature of an autonomous driving providing part that transmits the integrated high-precision map to the second moving object for autonomous driving as taught by Du, with a reasonable expectation of success, in order to provide an updated obstacle map to a moving vehicle with an obstructed view so that the vehicle can perceive the obstacles in the obstructed areas as specified in at least [0055] of Du.
For claim 11, Wong discloses wherein the integrated map generating part reflects the fixed position corresponding to the fixed object located in a terminal per yard in the integrated high- precision map (See at least pages 3-13 – “… the physical environment 100 includes a vehicle 102 coupled to a sensor array 108 as well as a mobile computer 104, a central computer 106, and the like. The sensor array 108 may analyze various objects within the physical environment 100 and may provide data (e.g., image data, video data, etc.) to the mobile computer 104… physical environment 100 also includes a plurality of markers 116… the plurality of markers 116 are beacons that enable environmental based navigation… mobile computer 104 extracts environmental features and determines an accurate, current vehicle pose… mobile computer 104 provides accurate position estimates for the industrial vehicle and updates the local map data 310 with information associated with environmental features… method 600 processes new features for landmark information associated with one or more industrial vehicles … patterns to be matched are selected from the geometric structures of known entities in the environment, such as pallets, loads, and so on… Landmarks represent the physical attributes of the environment that can be used for steering. The method 600 adds new landmarks to the map data … global map module 328 defines global map data 334 as a vector of known landmarks, which can be used to construct a vector of known features … one or more landmark locations are converted to locations in the common coordinate system… the method may generate a request to update the local map to add new features observed by other industrial vehicles…”).
For claim 13, Wong fails to specifically disclose wherein the integrated map generating part recognizes the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR, and reflects the positions of the plurality of first moving objects based on the plurality of first moving object markers in the integrated high-precision map.
However, Lee, in the same field of endeavor teaches wherein the integrated map generating part recognizes the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR, and reflects the positions of the plurality of first moving objects based on the plurality of first moving object markers in the integrated high-precision map (See at least page 16 of Lee – “…a current position of an object, a moving direction, and a moving speed may be obtained… each of the autonomous vehicles 1621-1, 1620-2, 1620-3, and 1620-4 may also generate information on surrounding objects… the control server may display information on an object in the HD Map based on information acquired from sensors of a plurality of autonomous vehicles or smart poles. That is, the control server can provide information on objects that change in real time along with the HD Map to the autonomous vehicle, and through this, the autonomous driving can be controlled…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on autonomous vehicles to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of recognizing the plurality of first moving object markers respectively corresponding to the plurality of first moving objects on the basis of the first moving object LiDAR as taught by Lee, with a reasonable expectation of success, in order to provide information on objects that change in real time along with the HD Map to the autonomous vehicle as specified in at least page 16 of Lee.
For claim 14, Wong fails to specifically disclose wherein the integrated map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR, and reflects the positions of the plurality of second moving objects based on the plurality of second moving object markers in the integrated high-precision map.
However, Du, in the same field of endeavor teaches wherein the integrated map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR, and reflects the positions of the plurality of second moving objects based on the plurality of second moving object markers in the integrated high-precision map (See at least [0055] – “… the first vehicle 510 employing a 360 degree camera detection system when travelling in a congested area will have a clear line of sight to some proximate objects 520, 530, 535, and will have an obstructed view 550 to some other proximate objects 540, 545. The system will use the detected information to generate an obstacle map of the local area… the proximate vehicle may generate an obstacle map relative to the proximate vehicles position and then broadcast this obstacle map to other vehicles via a V2X system or a dedicated short range communications (DSRC) system. In this fashion…the first vehicle 510 could detect and perceive the vehicle 540, 545, which is in an obstructed view 550 to first vehicle 510…” and [0066] of Du – “… system of an individual autonomous … vehicle may superimpose a first set of the detected road users through ego-sensors, such as camera sensors or Lidar… together with a second set of the detected road users by receiving V2X communications …”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Du teaches an autonomous driving system for vehicles that is able to detect other moving vehicles in an obstructed area of a vehicle and generate an obstacle map to transmit to the vehicle so that vehicle is aware of the other moving vehicles in the obstructed area.
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 autonomous driving map generation device as disclosed in Wong to include the feature of the integrated map generating part recognizes the plurality of second moving object markers respectively corresponding to the plurality of second moving objects on the basis of the second moving object LiDAR as taught by Du, with a reasonable expectation of success, in order to provide an updated obstacle map to a moving vehicle with an obstructed view so that the vehicle can perceive the obstacles in the obstructed areas as specified in at least [0055] of Du.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Wong in view of Lee and Du, as applied to claim 1 above, and further in view of Sadek et al. US 20230322259 A1 (“Sadek”).
For claim 6, Wong fails to specifically disclose wherein the fixed object includes a light tower located in a terminal.
However, Lee, in the same field of endeavor teaches wherein the fixed object includes a light tower located in a terminal (See at least pages 15-16 of Lee – “… the smart pole 1510 in the form of a street light… to perform various sensing…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on an autonomous vehicle to determine which map to use for autonomous driving.
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 autonomous driving map generation device as disclosed in Wong to include the feature of the fixed object includes a light tower located in a terminal as taught by Lee, with a reasonable expectation of success, in order to perform various sensing of the surrounding environment as specified in at least pages 15-16 of Lee.
Furthermore, Wong also fails to specifically disclose the fixed object marker with fixed GPS latitude and longitude values.
However, Sadek, in the same field of endeavor teaches the fixed object marker with fixed GPS latitude and longitude values (See at least [0079] of Sadek – “… In determining the position of the vehicle 102 within the map, the positioning engine layer 226 take into consideration confidence information regarding locations of objects and features within the map as well as confidence (e.g., accuracy and/or precision information) in sensor data used in the positioning engine layer … the map fusion and arbitration layer 230 may convert latitude and longitude information from GPS into locations within a surface map of roads contained in the map database and compare such locations to information received from radar, lidar and/or camera sensors that can identify and locate the objects and features associated with roads in the map data…”). Thus, Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles, while Sadek teaches a system that verifies and locates objects in a map using GPS latitude and longitude 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 modify the autonomous driving map generation device as disclosed in Wong to include the feature of the fixed object marker with fixed GPS latitude and longitude values as taught by Sadek, with a reasonable expectation of success, in order to locate the objects and features in the map data as specified in at least [0079] of Sadek.
Allowable Subject Matter
Claims 3, 7, and 12 are objected to for containing allowable subject matter, but would be allowable if the claim rejections from previous sections of this office action were resolved.
The following is an Examiner’s statement of reasons for allowance:
The closest prior art of record is Wong KR 101589943 B1 (“Wong”), Lee KR 102256541 B1 (“Lee”), Du et al. US 20190052842 A1 (“Du”), and Sadek et al. US 20230322259 A1 (“Sadek”).
Wong discloses a system for navigating autonomous industrial vehicles by generating map data including features of detected of an environment and updating the map data using information captured by industrial vehicles to share with other vehicles.
Lee teaches a system for navigating autonomous vehicles that generates high precision maps using lidars provided on fixed poles to map an environment and compares the high precision map generated by a server to the map generated using lidar sensors provided on an autonomous vehicle to determine which map to use for autonomous driving.
Du teaches an autonomous driving system for vehicles that is able to detect other moving vehicles in an obstructed area of a vehicle and generate an obstacle map to transmit to the vehicle so that vehicle is aware of the other moving vehicles in the obstructed area.
Sadek teaches a system that verifies and locates objects in a map using GPS latitude and longitude information.
As to claim 3, the prior art of record, taken individually or in combination, fails to teach or suggest the following claimed subject matter:
“wherein the first moving object-based map generating part recognizes the fixed object marker corresponding to the fixed object hidden by cargo blocks stacked in the terminal on the basis of the first moving object LiDAR, and additionally reflects the position of the fixed object based on the fixed object marker and the position of the hidden fixed object based on the hidden fixed object marker in the first high-precision map to generate the second high-precision map for autonomous driving”
As to claim 7, the prior art of record, taken individually or in combination, fails to teach or suggest the following claimed subject matter:
“wherein the first moving object includes a gantry crane or a transportable crane moving at a speed equal to or smaller than a predetermined first speed in a terminal, includes the first moving object marker having a relative position value and moving at the predetermined first speed, and includes a first moving object LiDAR that recognizes the fixed object marker, the hidden fixed object marker, and the first moving object marker”
As to claim 12, the prior art of record, taken individually or in combination, fails to teach or suggest the following claimed subject matter:
“wherein the integrated map generating part recognizes the hidden fixed object marker corresponding to the fixed object hidden by cargo blocks stacked in the terminal on the basis of the first moving object LiDAR, and reflects the position of the fixed object based on the fixed object marker and the position of the hidden fixed object based on the hidden fixed object marker, in the integrated high-precision map”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J HERRERA whose telephone number is (571)270-5271. The examiner can normally be reached M-F 10:00 AM to 6:00 PM EST.
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/M.J.H./Examiner, Art Unit 3668
/Fadey S. Jabr/Supervisory Patent Examiner, Art Unit 3668
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