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
This office action is in regards to application # 18/700,112 that was filed on 04/10/2024. Claims 1-10 are currently pending and are under examination.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Alsindi et al. (US 2011/0074569).
Regarding Claim 1, broadly interpreted, Alsindi discloses a multiple positioning apparatus, comprising:
a node setting part for setting at least three anchor nodes whose positions are known(set of anchors at known locations, anchor m (101), Fig. 3, abstract, Fig. 1) to at least one unknown node whose position is to be obtained (a set of sensors at unknown locations, sensor n (102), Fig. 3, abstract, Fig. 1);
an information acquisition part for acquiring distance information between each of unknown nodes and each of anchor nodes (310, Fig. 3), distance information between unknown nodes and coordinate information of each of anchor nodes (Fig. 1-3); and
a coordinate calculation part (360, Fig. 3)for calculating coordinates of each of the unknown nodes based on the distance information between each of the unknown nodes and each of the anchor nodes (310, Fig. 3), the distance information between the unknown nodes and the coordinate information of each of the anchor nodes.
Claim(s) 1-2 and 10is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Hohl (US2008/0309556).
Regarding Claim 1, Hohl discloses a multiple positioning apparatus (para. [0001]-[0005], [0023]-[0025], [0035]), comprising:
a node setting part for setting at least three anchor nodes whose positions are known to at least one unknown node whose position is to be obtained (discloses selecting a set of base nodes (anchor/reference nodes with known or reference positions that define the coordinate system) for localizing other unknown nodes in the network; para. [0001]-[0005], [0023]-[0025], [0035]-[0040], [0074]-[0080], [0096]-[0100]) ;
an information acquisition part for acquiring distance information between each of unknown nodes and each of anchor nodes, distance information between unknown nodes and coordinate information of each of anchor nodes (discloses nodes (including unknown/sensor nodes) measuring distances/ranges to neighboring exchanging distance reports and acquiring reference coordinate/positions of base/anchor nodes see[0023]-[0025], [0035]-[0040], [0078]-[0080]); and
a coordinate calculation part for calculating coordinates of each of the unknown nodes based on the distance information between each of the unknown nodes and each of the anchor nodes, the distance information between the unknown nodes and the coordinate information of each of the anchor nodes (discloses a computing relative 3D/2D coordinates of unknown nodes using the acquired distances (to anchors + peers) and base/anchor coordinates via trilateration, multilateration, bounding boxes, iterative etc. (see[0023]-[0025], [0035]-[0040], [0074]-[0080], [0096]-[0100], Fig. 1-2 and cited algorithms) .
Regarding Claim 2, Hohl discloses a multiple positioning apparatus (para. [0001]-[0005], [0023]-[0025], [0035]) wherein each of the unknown nodes is a sensor apparatus (para. [0023]-[0025]).
Regarding Claim 10, the method claim 10 is rejected under the same rational as the rejection of the apparatus claim 1 above.
Claim(s) 5 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Beko et al. (US 2018/0100915).
Regarding Claim 5, Beko discloses a multiple positioning apparatus (see para. [0001]-[0006], abstract), comprising:
a node setting part for setting at least three anchor nodes whose positions are known to at least one unknown node whose position is to be obtained (para. [0019]-[0022], [0030]-[0035], system uses multiple fixed anchor nodes with known positions to localize unknown target nodes/sensors) ;
an information acquisition part for acquiring distance and angle information (RSS for distance +AoA, merges RSS and AoA observations; RSS for substance/range and AoA (angle information)) between each of unknown nodes and each of anchor nodes, distance information between unknown nodes and coordinate information of each of anchor nodes (para. [0005], [0023]-[0025], [0036]-[0040], [0050]-[0060]); and
a coordinate calculation part for calculating coordinates of each of the unknown nodes based on the distance and angle information between each of the unknown nodes and each of the anchor nodes, the distance information between the unknown nodes and the coordinate information of each of the anchor nodes ((para. [0023]-[0025], [0036]-[0045], [0055]-[0070]; Hybrid RSS/AoA algorithm computes 3D coordinates of the unknown target using combined range(distance from RSS) and angle (AoA) measurements to multiple anchors, plus anchor coordinates).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hohl (US2008/0309556) in view of XUEMAI et al. (CN102158956B).
Regarding claim 3, Hohl do not explicitly detail assigning different weights to distance information in coordinate calculations. However XUEMAI teaches a weighted trilateration method in wireless sensor networks for improving positioning accuracy by assigning different weights to distance measurement (based on RSS/signal quality) between the unknown node and each anchor node( and implicitly using anchor coordinates),(see para. [0019]-[0022], steps 2-4, claims, the unknown node selects/sequences anchors and applies weight in the trilateral coordinate calculation).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Hohl’s coordinate calculation part by incorporating the weighting technique taught in XUEMAI with a reasonable expectation of success to improve accuracy and robustness, especially in noisy RF environments where some distance measurements are more reliable than others.
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hohl (US2008/0309556) in view of Wu et al. (US 7,821,453).
Regarding Claim 4, Hohl discloses the apparatus including coordinate calculations using distance to anchor for unknown nodes (para. [0023]-[0025], [0035]-[0040]). Hohl does not expressly disclose that the coordinates calculation part applies Extended Kalman Filter (EKF) to the distance information.
However, Wu teaches a distributed sensor fusion method for target localization that uses Extended Kalman Filter (EKF) to estimate the position of unknown targets/nodes by fusing distance/range measurements from multiple sensors/anchors with known positions (see abstract, col. 3-6, col 8-10).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Hohl’s coordinate calculation part by incorporating the EKF technique taught in Wu with a reasonable expectation of success to achieve better accuracy and robustness. Hohl already performs position estimation from noisy distance measurements and acknowledges the need for refinement/iteration. EKF provides a well known optimal recursive method for handling nonlinear measurement model and noise in range data. The combination yields predictable results: more accurate and stable coordinate estimate for unknown nodes using the same distance and anchor coordinate inputs.
Claim(s) 6-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beko et al. (US 2018/0100915) in view of Sinha (US 8,798,357).
Regarding Claims 6 and 7, Bako discloses a multiple positioning apparatus with anchors, distance/angle acquisitions and coordinate calculations as rejected in claim 5.
Bako is silent, but Sinha teaches the camera based image localization system comprising unknown nodes as a camera or image device as a moving/unknown node whose position is to be determined (see abstract, col. 1 lines 5-15; col. 2, line 50- col. 3, lines 20; col. 5 line 1- col. 6, line 30).
modified Bako is also silent, but Sinha teaches the camera based image localization system wherein anchor nodes are specific points in an image captured by the camera (known reference points, landmarks, or points in the image captured by the camera serve as anchors with known #D world positions for computing the camera’s pose/position (see col. 3, lines 30- col. 4, lines 60; col. 6 line 40- col. 8, lines 50; col. 9 line 10- col. 10, lines 40, using image features/points for 3D pose estimation)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the positioning apparatus of Beko by incorporating the camera based localization technique of Sinha with a reasonable expectation of success. The Beko system already uses distance and angle information from anchors, replacing or augmenting RF sensors with camera (where anchors are visual points in the captured image) is predictable substitution of known predictable modalities to achieve accurate localization in environments rich in visual features. This yields predictable results of improved or alternative positioning using image based measurements while retaining the core apparatus structure.
Regarding Claim 7, modified Bako is silent, but Sinha teaches the camera based image localization system wherein anchor nodes are specific points in an image captured by the camera (known reference points, landmarks, or points in the image captured by the camera serve as anchors with known #D world positions for computing the camera’s pose/position (see col. 3, lines 30- col. 4, lines 60; col. 6 line 40- col. 8, lines 50; col. 9 line 10- col. 10, lines 40, using image features/points for 3D pose estimation)
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beko et al. (US 2018/0100915) in view of XUEMAI et al. (CN102158956B).
Regarding claim 8, Beko do not explicitly detail assigning different weights to distance information in coordinate calculations. However XUEMAI teaches a weighted trilateration method in wireless sensor networks for improving positioning accuracy by assigning different weights to distance measurement (based on RSS/signal quality) between the unknown node and each anchor node( and implicitly using anchor coordinates),(see para. [0019]-[0022], steps 2-4, claims, the unknown node selects/sequences anchors and applies weight in the trilateral coordinate calculation).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Beko’s coordinate calculation part by incorporating the weighting technique taught in XUEMAI with a reasonable expectation of success to improve accuracy and robustness, especially in noisy RF environments where some distance measurements are more reliable than others.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Beko et al. (US 2018/0100915)in view of Wu et al. (US 7,821,453).
Regarding Claim 9, Beko discloses the apparatus including coordinate calculations using distance to anchor for unknown nodes (see para. [0001]-[0006], abstract). Beko does not expressly disclose that the coordinates calculation part applies Extended Kalman Filter (EKF) to the distance and angle information.
However, Wu teaches a distributed sensor fusion method for target localization that uses Extended Kalman Filter (EKF) to estimate the position of unknown targets/nodes by fusing distance/range measurements from multiple sensors/anchors with known positions (see abstract, col. 3-6, col 8-10).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify Beko’s coordinate calculation part by incorporating the EKF technique taught in Wu with a reasonable expectation of success to achieve better accuracy and robustness. Beko already performs position estimation from noisy distance and angle measurements and acknowledges the need for refinement/iteration. EKF provides a well-known optimal recursive method for handling nonlinear measurement model and noise in range and angle data. The combination yields predictable results: more accurate and stable coordinate estimate for unknown nodes using the same distance, angle, and anchor coordinate inputs.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Lou et al. (US 11,536,554) discloses a similar localization and attitude estimation method, but using magnetic fields including the following steps. First, in three-dimensional coordinates, at least three magnetic landmarks arbitrarily disposed around a moving carrier are selected, wherein any two of the at least three magnetic landmarks have different magnetic directions. One set of at least five tri-axes magnetic sensors is used to sense the magnetic fields of the at least three magnetic landmarks. Three magnetic components on three axes of a current position of each of the tri-axes magnetic sensors are respectively generated by a demagnetization method. Five non-linear magnetic equations are solved to obtain position information and magnetic moment information of the at least three magnetic landmarks in the three-dimensional coordinates. Position vectors and attitude vectors of the set of at least five tri-axes magnetic sensors in a three-dimensional space are estimated based on tri-axes magnetic moment vectors of the magnetic landmarks. .
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Assres H. Woldemaryam
Primary Examiner (Aeronautics and Astronautics)
Art Unit 3642
/ASSRES H WOLDEMARYAM/Primary Examiner, Art Unit 3642
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