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 .
DETAILED ACTION
Response to Amendment
The amendment filed 12/05/2025 has been entered. Claims 1-2 and 5-8 are pending in the application. Applicant’s amendments to the claims have overcome each and every objection previously set forth in the Non-Final Action mailed 09/05/2025.
Response to Arguments
Applicant's arguments filed 12/05/2025 have been fully considered but they are not persuasive. In the applicant’s remarks, see pages 8-11, the applicant argues that the previously listed prior arts Kiyota in view of Sawada, Shah, and Iwase do not teach the limitation “a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape… derived from a specification of the moving body parts stored in memory”. The examiner respectfully disagrees.
Prior art Iwase teaches a masking range L which is set to “a three-dimensional range in the front-rear, left-right, and up-down directions”, for example, a “range Lc in which the work device 12 is located”, which is rectangular, as seen on Fig. 14, such that a 3D view of the masking range is a rectangular parallelepiped, as the range is described to be “three-dimensional” (Iwase, Para. 0087), constituting “a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape”. The applicant argues Fig. 14 to be a part of a “2D process”, however, Iwase teaches that Fig. 14 is part of a three-dimensional process, see “a three-dimensional image generated from a measurement result of the rear lidar sensor” (Iwase, Para. 0057). Furthermore, in regards to the amended limitation “wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derived from a specification of the moving body parts stored in memory”, Iwase teaches setting a “masking range” based on an “acquired range of movement of the front wheels 5 and the front work device 120”, or a specification of the moving body parts, where the “acquired range of movement” is stored in “the vehicle-mounted storage unit”. A “masking range setting unit” of Iwase then “sets the masking range L in accordance with the range of movement” of the moving body parts, for example a front work device (Iwase, Para. 0186, 0192-0193, 0198, and 0204). Therefore, Iwase teaches the limitation “a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape… derived from a specification of the moving body parts stored in memory”.
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.
Claim(s) 1, 5, and 6 are rejected under 35 U.S.C. 103 as being unpatentable over of Kiyota, et al., hereinafter Kiyota (U.S. Patent Application Pub. No. 2018/0258616) in view of Sawada (Japanese Patent Application Pub. No. 2018-142756), and further in view of Shah et al., hereinafter Shah (U.S. Patent Application Pub. No. 2019/0194005) and Iwase, et al., hereinafter Iwase (Japanese Patent Application Pub. No. 2020-035112).
Regarding Claim 1, Kiyota teaches: An obstacle detector for being mounted on a moving body (Kiyota, Para. 0054 – “a surroundings monitoring system” which is “mounted” on a “construction machine”, or moving body) comprising:
a sensor configured to capture a detection result of an environment (Kiyota, Para. 0054-0058 – an “image capturing apparatus” which is “an apparatus to capture an image of the surroundings of the shovel” of a “construction machine”), wherein a portion of the moving body is captured in the detection result (Kiyota, Para. 0079-0080 – where a captured “image region” may include “a region into which the body of the shovel is captured (hereinafter “body captured region”)”); where the body of the shovel is part of the construction machine, or moving body), and to detect an obstacle (Kiyota, Para. 0057 – where a “controller” utilizes the “image capturing apparatus” to determine “whether a person”, or obstacle, “is present around the shovel”); and
a position detection unit configured to detect a position of the obstacle from a detection result of the sensor (Kiyota, Para. 0067-0068 – where the controller performs a “normalizing process” and determines a “standing position of a person” utilizing the “captured image”), wherein the position detection unit includes:
a coordinate deriving unit configured to derive coordinates of where Fig. 5 shows a “top plan view of a real space” having a virtual grid, utilized by the controller, at the back of a work vehicle and a person, or obstacle, is shown in the real space, or coordinate system; where as shown on Fig. 4, the obstacle is measured on three axes, such that the coordinate system is three dimensional), wherein the three-dimensional coordinate system has an X-axis extending in one direction of a horizontal direction, a Y-axis extending in an orthogonal direction to the X-axis of the horizontal direction, and a Z-axis extending orthogonal to the X- axis and Y-axis (Kiyota, Figs. 4-5 and Para. 0072 and 0189– where the person, or obstacle, is represented as in a box BX that is measured using grid points on axes which are “orthogonal” to each other; where the “three-dimensional position (an actual location)” of the person, or obstacle, is determined),
a non-detection unit configured to remove one or more feature “the extracting part 31 masks the image of an identification process unsuitable region included in the target image region”, where the “identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”; where as shown on Fig. 4, the obstacle is measured on three axes, such that the coordinate system is three dimensional) and that is set in advance in a detectable area where the obstacle is detectable by the sensor (Kiyota, Para. 0080 – where according to one embodiment, the “extracting part 31 masks these identification process unsuitable regions and thereafter generates the normalized image TRgt5 of a target image having the target image region”, such that the masking of the unsuitable regions, or non-detection areas, occurs before the detecting within the target image region), such that the obstacle will be determined to not be present, regardless of the detection result of the sensor (Kiyota, Para. 0081-0082 and 0087 – where the “masked regions” are not utilized during an “identification process” of a person, or obstacle; i.e. “the identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions”)
a detection unit configured to detect, “a process of extracting a target image that is highly likely to include a prospective person”, or obstacle, “image by the extracting part” where “the identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”); and
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While Kiyota teaches a coordinate deriving unit configured to derive coordinates of the obstacle, and a non-detection unit configured to remove one or more features that are present in a non-detection area which represents an area in which the portion of the moving body is present in the three-dimensional coordinate system of the environment, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory Kiyota does not teach derive coordinates of Additionally, Kiyota does not teach detect, based on the plurality of feature points, the position of the obstacle present, nor does Kiyota teach wherein when coordinates of the obstacle in the three-dimensional coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present, .
However, Sawada teaches wherein when coordinates of the obstacle in the coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present (Sawada, Para. 0066-0068 and 0081 – where a “determination exclusion region” is set, and a “recognition target object” is detected in a “detected image”, where it is determined whether the detected image overlaps, or is within, the determination exclusion image, and if so, the overlapping target object within the exclusion region is “excluded from the determination process”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the obstacle detector of Kiyota to include wherein when coordinates of the obstacle in the coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present, as taught by Sawada, in order to provide a method of excluding a detected “obstacle” within a non-detection area where the moving body is located without modifying a detection process by a sensor and to prevent erroneous recognition of the moving body as an obstacle.
Kiyota in view of Sawada does not teach derive coordinates of a plurality of feature points corresponding to the obstacle, and remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, and detect, based on the plurality of feature points, the position of the obstacle present, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Shah teaches derive coordinates of a plurality of feature points corresponding to the obstacle (Shah, Para. 0004 and 0133 – a control system including sensors which detect “sensor data points representing a position of a face of a pallet within an environment” where the sensor points include “the coordinates of each of the plurality of sensor data points”), and remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area (Shah, Para. 0107 and 0157 – the “initial plurality of sensor data points may be filtered by removing positions outside of the determined zone of interest”, such that the area outside of the “zone of interest” is a non-detection area), and detect, based on the plurality of feature points, the position of the obstacle present in a detection area (Shah, Para. 0107-0108 and 0157-0161 – based on the remaining sensor data points following the removal, cited above, determine “a position of a face of a pallet within an environment” and monitor “changes in position and orientation of pallet”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detector including the above limitations of Kiyota in view of Sawada to include derive coordinates of a plurality of feature points corresponding to the obstacle, and remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area, and detect, based on the plurality of feature points, the position of the obstacle present in a detection area, as taught by Sugimoto, in order to remove erroneous feature points to irrelevant data and improve calculation speed and performance by reducing such points.
Kiyota in view of Sawada and Shah does not teach a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Iwase teaches a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape (Iwase, Para. 0087 – “the masking range L is set to a three-dimensional range in the front-rear, left-right, and up-down directions”, for example, “the range Lc in which the work device 12 is located”, which is rectangular, as seen on Fig. 14, such that a 3D view of the masking range is a rectangular parallelepiped), wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory (Iwase, Para. 0087, 0186, 0192-0193, 0198, and 0204 – setting a “masking range” based on an “acquired range of movement of the front wheels 5 and the front work device 120”, or a specification of the moving body parts, where the “acquired range of movement” is stored in “the vehicle-mounted storage unit”; a “masking range setting unit” then “sets the masking range L in accordance with the range of movement” of the moving body parts, for example a front work device, where the “the masking range L is set to a three-dimensional range).
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detector including the above limitations of Kiyota in view of Sawada and Shah to include a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory, as taught by Iwase, in order to utilize a three-dimensional non-detection area to prevent erroneous detection of the moving body as an obstacle in all three dimensions.
Regarding Claim 5, Kiyota teaches: An obstacle detection method of detecting a position of an obstacle by an obstacle detector that includes a sensor and a position detection unit and is mounted on a moving body (Kiyota, Para. 0004, 0054, and 0067-0068 – “a surroundings monitoring system” which is “mounted” on a “construction machine”, or moving body, having a controller and processor configured to “detect an obstacle present around the work machine”), the obstacle detection method comprising:
a step in which the position detection unit obtains a detection result of an environment captured by the sensor (Kiyota, Para. 0054-0058 – an “image capturing apparatus” which is “an apparatus to capture an image of the surroundings of the shovel” of a “construction machine”), wherein a portion of the moving body is captured by the detection result (Kiyota, Para. 0079-0080 – where a captured “image region” may include “a region into which the body of the shovel is captured (hereinafter “body captured region”)”);
a step in which coordinates of where Fig. 5 shows a “top plan view of a real space” having a virtual grid, utilized by the controller, at the back of a work vehicle and a person, or obstacle, is shown in the real space, or coordinate system), wherein the coordinate system has an X-axis extending in one direction of a horizontal direction, a Y-axis extending in an orthogonal direction to the X-axis of the horizontal direction, and a Z-axis extending orthogonal to the X-axis and the Y-axis (Kiyota, Figs. 4-5 and Para. 0072 and 0189– where the person, or obstacle, is represented as in a box BX that is measured using grid points on axes which are “orthogonal” to each other; where the “three-dimensional position (an actual location)” of the person, or obstacle, is determined);
a step in which the position detection unit determines that the obstacle is not present, regardless of the detection result of the sensor, in a non-detection area “the extracting part 31 masks the image of an identification process unsuitable region included in the target image region”, where the “identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”) and that is set in advance in a detectable area where the obstacle is detectable by the sensor (Kiyota, Para. 0080 – where according to one embodiment, the “extracting part 31 masks these identification process unsuitable regions and thereafter generates the normalized image TRgt5 of a target image having the target image region”, such that the masking of the unsuitable regions, or non-detection areas, occurs before the detecting within the target image region),
a step in which the position detection unit detects, “a process of extracting a target image that is highly likely to include a prospective person”, or obstacle, “image by the extracting part” where “the identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”);
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While Kiyota teaches a step in which coordinates of obstacle in a three-dimensional coordinate system of the environment are derived, and a non-detection area which represent an area in which the portion of the moving body is present in the coordinate system of the environment, Kiyota does not teach coordinates of a plurality of feature points corresponding to the obstacle, and a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, and detects, based on the plurality of feature points, the position of the obstacle present in a detection area, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory. Additionally, Kiyota does not teach wherein, in the step in which the position detection unit determines that the obstacle is not present, regardless of the detection result of the sensor, in the non-detection area, the non-detection unit determines that the obstacle represented by the plurality of feature points is not present based on removing one or more feature points, from among the plurality of feature points, that are present in the non-detection area of the three-dimensional coordinate system of the environment.
However, Sawada teaches wherein, in the step in which the position detection unit determines that the obstacle is not present, regardless of the detection result of the sensor, in the non-detection area, the non-detection unit determines that the obstacle is not present in the non-detection area (Sawada, Para. 0066-0068 and 0081 – where a “determination exclusion region” is set, and a “recognition target object” is detected in a “detected image”, where it is determined whether the detected image overlaps, or is within, the determination exclusion image, and if so, the overlapping target object within the exclusion region is “excluded from the determination process”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the obstacle detection method of Kiyota to include wherein, in the step in which the position detection unit determines that the obstacle is not present, regardless of the detection result of the sensor, in the non-detection area, the non-detection unit determines that the obstacle is not present in the non-detection area, as taught by Sawada, in order to provide a method of excluding a detected “obstacle” within a non-detection area where the moving body is located without modifying a detection process by a sensor and to prevent erroneous recognition of the moving body as an obstacle.
Kiyota in view of Sawada does not teach coordinates of a plurality of feature points corresponding to the obstacle, and a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, detect, based on the plurality of feature points, the position of the obstacle present in a detection area, and the non-detection unit determines that the obstacle represented by the plurality of feature points is not present based on removing one or more feature points, from among the plurality of feature points, that are present in the non-detection area, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Shah teaches coordinates of a plurality of feature points corresponding to the obstacle (Shah, Para. 0004 and 0133 – a control system including sensors which detect “sensor data points representing a position of a face of a pallet within an environment” where the sensor points include “the coordinates of each of the plurality of sensor data points”), the non-detection unit determines that the obstacle represented by the plurality of feature points is not present based on removing one or more feature points, from among the plurality of feature points, that are present in the non-detection area (Shah, Para. 0107 and 0157 – the “initial plurality of sensor data points may be filtered by removing positions outside of the determined zone of interest”, such that the area outside of the “zone of interest” is a non-detection area), and detect, based on the plurality of feature points, the position of the obstacle present in a detection area (Shah, Para. 0107-0108 and 0157-0161 – based on the remaining sensor data points following the removal, cited above, determine “a position of a face of a pallet within an environment” and monitor “changes in position and orientation of pallet”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detection method including the above limitations of Kiyota in view of Sawada to include coordinates of a plurality of feature points corresponding to the obstacle, the non-detection unit determines that the obstacle represented by the plurality of feature points is not present based on removing one or more feature points, from among the plurality of feature points, that are present in the non-detection area, and detect, based on the plurality of feature points, the position of the obstacle present in a detection area, as taught by Sugimoto, in order to remove erroneous feature points to irrelevant data and improve calculation speed and performance by reducing such points.
Kiyota in view of Sawada and Shah does not teach a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Iwase teaches a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape (Iwase, Para. 0087 – “the masking range L is set to a three-dimensional range in the front-rear, left-right, and up-down directions”, for example, “the range Lc in which the work device 12 is located”, which is rectangular, as seen on Fig. 14, such that a 3D view of the masking range is a rectangular parallelepiped), wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory (Iwase, Para. 0087, 0186, 0192-0193, 0198, and 0204 – setting a “masking range” based on an “acquired range of movement of the front wheels 5 and the front work device 120”, or a specification of the moving body parts, where the “acquired range of movement” is stored in “the vehicle-mounted storage unit”; a “masking range setting unit” then “sets the masking range L in accordance with the range of movement” of the moving body parts, for example a front work device, where the “the masking range L is set to a three-dimensional range).
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It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detection method including the above limitations of Kiyota in view of Sawada and Shah to include a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory, as taught by Iwase, in order to utilize a three-dimensional non-detection area to prevent erroneous detection of the moving body as an obstacle in all three dimensions.
Regarding Claim 6, Kiyota teaches: An obstacle detector for being mounted on a moving body (Kiyota, Para. 0054 – “a surroundings monitoring system” which is “mounted” on a “construction machine”, or moving body) comprising:
a sensor configured to capture a detection result of an environment (Kiyota, Para. 0054-0058 – an “image capturing apparatus” which is “an apparatus to capture an image of the surroundings of the shovel” of a “construction machine”), wherein a portion of the moving body is captured in the detection result (Kiyota, Para. 0079-0080 – where a captured “image region” may include “a region into which the body of the shovel is captured (hereinafter “body captured region”)”), and to detect an obstacle (Kiyota, Para. 0057 – where a “controller” utilizes the “image capturing apparatus” to determine “whether a person”, or obstacle, “is present around the shovel”);
at least one memory configured to store computer program code (Kiyota, Para. 0056 – a controller including “an internal memory” which stores “a drive control program”); and
at least one processor configured to access the at least one memory and operate as instructed by the computer program code (Kiyota, Para. 0056 – where a controller includes a “CPU” which executes “a drive control program stored in the internal memory”), the computer program code including
position detection code configured to cause the at least one processor to detect a position of the obstacle from a detection result of the sensor (Kiyota, Para. 0067-0068 – where the controller performs a “normalizing process” and determines a “standing position of a person” utilizing the “captured image”), wherein the position detection code includes:
coordinate deriving code configured to cause the at least one processor to derive coordinates of where Fig. 5 shows a “top plan view of a real space” having a virtual grid, utilized by the controller, at the back of a work vehicle and a person, or obstacle, is shown in the real space, or coordinate system), wherein the three-dimensional coordinate system has an X-axis extending in one direction of a horizontal direction, a Y-axis extending in an orthogonal direction to the X-axis of the horizontal direction, and a Z-axis extending orthogonal to the X-axis and Y-axis (Kiyota, Figs. 4-5 and Para. 0072 and 0189– where the person, or obstacle, is represented as in a box BX that is measured using grid points on axes which are “orthogonal” to each other; where the “three-dimensional position (an actual location)” of the person, or obstacle, is determined),
non-detection code configured to cause the at least one processor to remove one or more feature “the extracting part 31 masks the image of an identification process unsuitable region included in the target image region”, where the “identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”) where according to one embodiment, the “extracting part 31 masks these identification process unsuitable regions and thereafter generates the normalized image TRgt5 of a target image having the target image region”, such that the masking of the unsuitable regions, or non-detection areas, occurs before the detecting within the target image region),
detection code configured to cause the at least one processor to detect, “a process of extracting a target image that is highly likely to include a prospective person”, or obstacle, “image by the extracting part” where “the identifying part 32 can identify whether it is a person image, using the image of a region other than masked regions in a normalized image without being affected by the images of identification process unsuitable regions including the body captured region”), and
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While Kiyota teaches a non-detection area which represent an area in which the portion of the moving body is present in the coordinate system of the environment, Kiyota does not teach derive coordinates of a plurality of feature points corresponding to the obstacle, remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, and detect, based on the plurality of feature points, the position of the obstacle present in a detection area. Additionally, Kiyota does not teach wherein when coordinates of the obstacle in the three-dimensional coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present, and remove features such that the obstacle will not be determined present, regardless of the detection result of the sensor, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Sawada teaches wherein when coordinates of the obstacle in the three-dimensional coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present, and remove features such that the obstacle will not be determined present, regardless of the detection result of the sensor (Sawada, Para. 0066-0068 and 0081 – where a “determination exclusion region” is set, and a “recognition target object” is detected in a “detected image”, where it is determined whether the detected image overlaps, or is within, the determination exclusion image, and if so, the overlapping target object within the exclusion region is “excluded from the determination process”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the obstacle detector of Kiyota to include wherein when coordinates of the obstacle in the coordinate system of the environment are in the non-detection area, the obstacle represented by the coordinates is determined to not be present, and remove features such that the obstacle will not be determined present, regardless of the detection result of the sensor, as taught by Sawada, in order to provide a method of excluding a detected “obstacle” within a non-detection area where the moving body is located without modifying a detection process by a sensor and to prevent erroneous recognition of the moving body as an obstacle.
Kiyota in view of Sawada does not teach derive coordinates of a plurality of feature points corresponding to the obstacle, remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory, and detect, based on the plurality of feature points, the position of the obstacle present in a detection area.
However, Shah teaches derive coordinates of a plurality of feature points corresponding to the obstacle (Shah, Para. 0004 and 0133 – a control system including sensors which detect “sensor data points representing a position of a face of a pallet within an environment” where the sensor points include “the coordinates of each of the plurality of sensor data points”), remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area (Shah, Para. 0107 and 0157 – the “initial plurality of sensor data points may be filtered by removing positions outside of the determined zone of interest”, such that the area outside of the “zone of interest” is a non-detection area), and detect, based on the plurality of feature points, the position of the obstacle present in a detection area (Shah, Para. 0107-0108 and 0157-0161 – based on the remaining sensor data points following the removal, cited above, determine “a position of a face of a pallet within an environment” and monitor “changes in position and orientation of pallet”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detector including the above limitations of Kiyota in view of Sawada to include derive coordinates of a plurality of feature points corresponding to the obstacle, remove one or more feature points, from among the plurality of feature points, that are present in a non-detection area, and detect, based on the plurality of feature points, the position of the obstacle present in a detection area, as taught by Sugimoto, in order to remove erroneous feature points to irrelevant data and improve calculation speed and performance by reducing such points.
Kiyota in view of Sawada and Shah does not teach a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory.
However, Iwase teaches a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape (Iwase, Para. 0087 – “the masking range L is set to a three-dimensional range in the front-rear, left-right, and up-down directions”, for example, “the range Lc in which the work device 12 is located”, which is rectangular, as seen on Fig. 14, such that a 3D view of the masking range is a rectangular parallelepiped), wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory (Iwase, Para. 0087, 0186, 0192-0193, 0198, and 0204 – setting a “masking range” based on an “acquired range of movement of the front wheels 5 and the front work device 120”, or a specification of the moving body parts, where the “acquired range of movement” is stored in “the vehicle-mounted storage unit”; a “masking range setting unit” then “sets the masking range L in accordance with the range of movement” of the moving body parts, for example a front work device, where the “the masking range L is set to a three-dimensional range).
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Iwase, Fig. 14
It would have been obvious to one of ordinary skill in the art before the effective filing date of the effective filing date of the claimed invention to have further modified the obstacle detector including the above limitations of Kiyota in view of Sawada and Shah to include a non-detection area that is defined by three-dimensional coordinates of a rectangular parallelepiped shape, wherein the three-dimensional coordinates of the rectangular parallelepiped shape are derive from a specification of the moving body stored in memory, as taught by Iwase, in order to utilize a three-dimensional non-detection area to prevent erroneous detection of the moving body as an obstacle in all three dimensions.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Kiyota in view of Sawada, Shah, and Iwase, and further in view of Teranishi, et al., hereinafter Teranishi (U.S. Patent Application Pub. No. 2022/0219954).
In regards to Claim 2, Kiyota in view of Sawada, Shah, and Iwase teaches the obstacle detector of Claim 1, and Kiyota teaches wherein the moving body is a forklift, and the non-detection area is set to a position at which a part of the forklift is present (Kiyota, Para. 0079-0082 and 0281 – where a region is masked to exclude a body structure of a machine, where the work machine can be a forklift).
However, Kiyota in view of Sawada, Shah, and Iwase does not teach a non-detection area is set to a position at which a counterweight is present.
Teranishi teaches a non-detection area is set to a position at which a counterweight is present (Teranishi, Para. 0010, 0111, 0233-0236, and 0277 – where “invalid areas”, or non-detection areas, are determined such that “it is determined that the obstacle is not detected regardless of the detection result of the obstacle detection device” in the invalid area; where the invalid areas are located in “monitoring areas” which include movable parts of a work machine; and where the movable part in the monitoring area can be a “counterweight”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the obstacle detector including wherein the moving body is a forklift, and the non-detection area is set to a position at which a part of the forklift is present, as taught by Kiyota in view of Sawada, Shah, and Iwase to include a non-detection area is set to a position at which a counterweight is present, as taught by Teranishi, in order to include a counterweight, which is commonly found in forklifts to counter the load carried on forks of a forklift, in a non-detection area, such that the counterweight is not falsely identified as an obstacle and does not cause a false stop of the operation of the forklift.
Claim 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Kiyota in view of Sawada, Shah, and Iwase, and further in view of Maeda (U.S. Patent Application Pub. No. 2020/0258253) and Yamaguchi, et al., hereinafter Yamaguchi (U.S. Patent Application Pub. No. 2017/0107698).
Regarding Claim 7, Kiyota in view of Sawada, Shah, and Iwase teaches the obstacle detector of Claim 1, but Kiyota does not teach wherein: the sensor is a stereo camera, the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity, and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit.
However, Maeda teaches wherein: the sensor is a stereo camera (Maeda, Para. 0051 – a “distance measurement unit” sensor for “measuring the distance to a target object”, and may include “a stereo camera”), and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit (Maeda, Para. 0083-0089 and 0097-0098 – where the “distance measurement unit” “outputs the acquired point group distance measurement data to the clustering unit” and the “clustering unit” “outputs the position information of the point group clusters representing the target object”; where in a case where a generated “self-shape part (part of an attachment instrument, an arm, and the like) is excluded” and the “self-shape part is a non-target object” positioned “in front of the target object”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the obstacle detector of Kiyota in view of Sawada and Gavrilovic to include wherein: the sensor is a stereo camera, and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit, as taught by Maeda, in order to provide a image sensor capable of capturing three dimensional images to provide further information of the obstacle’s location to the obstacle detector.
Kiyota in view of Sawada, Shah, Iwase, and Maeda does not teach the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity.
However, Yamaguchi teaches the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity (Yamaguchi, Para. 0045, 0053, and 0069 – “measuring a position of the object by a stereo system, the position of the object, for example, a three-dimensional position is acquired from the two images obtained by observing the same object from the two different imaging devices”, where a “disparity” is determined using the pair of two images; where the imaging devices have “coordinate system (Xs, Ys, Zs)”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the obstacle detector of Kiyota in view of Sawada, Gavrilovic, and Maeda to include the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity, as taught by Yamaguchi, in order to account for the difference in coordinates of two captured images in a stereo camera to obtain an accurate position of an obstacle.
Regarding Claim 8, Kiyota in view of Sawada, Shah, and Iwase teaches the obstacle detector of Claim 2, but Kiyota does not teach wherein: the sensor is a stereo camera, the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity, and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit.
However, Maeda teaches wherein: the sensor is a stereo camera (Maeda, Para. 0051 – a “distance measurement unit” sensor for “measuring the distance to a target object”, and may include “a stereo camera”), and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit (Maeda, Para. 0083-0089 and 0097-0098 – where the “distance measurement unit” “outputs the acquired point group distance measurement data to the clustering unit” and the “clustering unit” “outputs the position information of the point group clusters representing the target object”; where in a case where a generated “self-shape part (part of an attachment instrument, an arm, and the like) is excluded” and the “self-shape part is a non-target object” positioned “in front of the target object”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the obstacle detector of Kiyota in view of Sawada, Shah, and Iwase to include wherein: the sensor is a stereo camera, and the position detection unit is configured to detect the position of the obstacle by clustering of the obstacle coordinates excluding the obstacle coordinates which are determined to be present in the non-detection area by the non-detection unit, as taught by Maeda, in order to provide a image sensor capable of capturing three dimensional images to provide further information of the obstacle’s location to the obstacle detector.
Kiyota in view of Sawada, Shah, Iwase and Maeda does not teach the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity.
However, Yamaguchi teaches the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity (Yamaguchi, Para. 0045, 0053, and 0069 – “measuring a position of the object by a stereo system, the position of the object, for example, a three-dimensional position is acquired from the two images obtained by observing the same object from the two different imaging devices”, where a “disparity” is determined using the pair of two images; where the imaging devices have “coordinate system (Xs, Ys, Zs)”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified the obstacle detector of Kiyota in view of Sawada, Shah, Iwase and Maeda to include the position detection unit is configured to calculate a disparity by comparing a first image and a second image obtained as the detection result from the stereo camera and obtains the coordinates of the obstacle in the three-dimensional coordinate system coordinate system of the environment from the disparity, as taught by Yamaguchi, in order to account for the difference in coordinates of two captured images in a stereo camera to obtain an accurate position of an obstacle.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Voisin, et al. (U.S. Patent Application Pub. No. 2022/0100192) teaches a self-guided handling apparatus comprising a means for detecting obstacles.
Ishikawa, et al. (U.S. Patent Application Pub. No. 2020/0250831) teaches a human detection system for a work vehicle, including a mask region, the main body portion of the rough terrain crane included in the monitored region, and excludes the mask region from detection region D for obstacle detection.
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/H.L./Examiner, Art Unit 3665
/HUNTER B LONSBERRY/Supervisory Patent Examiner, Art Unit 3665
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