Method and apparatus for identifying critical parameters of a localization framework based on an input data source

US11080311B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-11080311-B2
Application numberUS-201816227647-A
CountryUS
Kind codeB2
Filing dateDec 20, 2018
Priority dateDec 20, 2018
Publication dateAug 3, 2021
Grant dateAug 3, 2021

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Abstract

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Methods described herein relate to identifying critical parameters of a localization framework that may require tuning for accuracy of the localization framework based on the data source. Methods may include: receiving a data set from a data source; comparing the data set against data stored in a database; identifying, based on the comparison, a subset of parameters of a localization framework for the data set from among a plurality of parameters of the localization framework; providing for tuning of the subset of parameters of the localization framework for the data set to generate a tuned subset of parameters; processing the data set from the data source using the localization framework including the tuned subset of parameters; and receiving an indication of a location from the localization framework of the data set within a mapped region.

First claim

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That which is claimed: 1. An apparatus comprising at least one processor and at least one non-transitory memory including computer program code instructions, the computer program code instructions configured to, when executed, cause the apparatus to at least: receive a data set from a data source; compare the data set against data stored in the memory; identify, based on the comparison, a subset of parameters of a localization framework for the data set from among a plurality of parameters of the localization framework, wherein the subset of parameters are identified based on a predefined similarity of a sensor configuration of the data source with a sensor configuration of a historical data source of the data stored in the memory; provide for tuning of the subset of parameters of the localization framework for the data set to generate a tuned subset of parameters; process the data set from the data source using the localization framework including the tuned subset of parameters; receive an indication of a location from the localization framework of the data set within a mapped region; and provide for an update of a map database of the mapped region based on the data set and the location of the data set within the mapped region. 2. The apparatus of claim 1 , wherein causing the apparatus to compare the data set against data stored in the memory comprises causing the apparatus to: determine a data type of the data set; compare, via a data similarity module, the data type against stored data types; and identify, based on the comparison, a stored data type similar to the data type of the data set, wherein a set of parameters identified as critical parameters for the stored data type similar to the data type of the data set is identified as the subset of parameters of the localization framework for the data set. 3. The apparatus of claim 1 , wherein the apparatus is further caused to: provide for storage in the memory of a data type of the data set; and provide for storage of the tuned subset of parameters of the localization framework associated with the data type of the data set. 4. The apparatus of claim 1 , wherein the data source comprises a first sensor configuration, wherein causing the apparatus to compare the data set against data stored in the memory comprises causing the apparatus to identify data stored in the memory associated with a second sensor configuration that is within a predefined degree of similarity to the first sensor configuration. 5. The apparatus of claim 1 , wherein causing the apparatus to compare the data set against data stored in the memory comprises causing the apparatus to: identify two or more historical data sources similar to the data source from which the data set is received; identify a subset of parameters of the localization framework for each of the two or more historical data sources; and interpolate among the subset of parameters of the localization framework for each of the two or more historical data sources to generate a subset of parameters of the localization framework for the data set. 6. The apparatus of claim 1 , wherein the data source comprises a data type identifying a sensor configuration of the data source. 7. The apparatus of claim 6 , wherein causing the apparatus to provide for tuning of the subset of parameters of the localization framework for the data set comprises causing the apparatus to provide for tuning of the subset of parameters according to the sensor configuration of the data source. 8. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-executable program code instructions stored therein, the computer-executable program code instructions comprising program code instructions to: receive a data set from a data source; compare the data set against data stored in a database; identify, based on the comparison, a subset of parameters of a localization framework for the data set from among a plurality of parameters of the localization framework, wherein the subset of parameters are identified based on a predefined similarity of a sensor configuration of the data source with a sensor configuration of a historical data source of the data stored in the memory; provide for tuning of the subset of parameters of the localization framework for the data set to generate a tuned subset of parameters; process the data set from the data source using the localization framework including the tuned subset of parameters; receive an indication of a location from the localization framework of the data set within a mapped region; and provide for an update of a map database of the mapped region based on the data set and the location of the data set within the mapped region. 9. The computer program product of claim 8 , wherein the program code instructions to compare the data set against data stored in the database comprises program code instructions to: determine a data type of the data set; compare, via a data similarity module, the data type against stored data types; and identify, based on the comparison, a stored data type similar to the data type of the data set, wherein a set of parameters identified as critical parameters for the stored data type similar to the data type of the data set is identified as the subset of parameters of the localization framework for the data set. 10. The computer program product of claim 8 , further comprising program code instructions to: provide for storage in the memory of a data type of the data set; and provide for storage of the tuned subset of parameters of the localization framework associated with the data type of the data set. 11. The computer program product of claim 8 , wherein the data source comprises a first sensor configuration, wherein the program code instructions to compare the data set against data stored in the database comprise program code instructions to identify data stored in the database associated with a second sensor configuration that is within a predefined degree of similarity to the first sensor configuration. 12. The computer program product of claim 8 , wherein the program code instructions to compare the data set against data stored in the database comprise program code instructions to: identify two or more historical data sources similar to the data source from which the data set is received; identify a subset of parameters of the localization framework for each of the two or more historical data sources; and interpolate among the subset of parameters of the localization framework for each of the two or more historical data sources to generate a subset of parameters of the localization framework for the data set. 13. The computer program product of claim 8 , wherein the data source comprises a data type identifying a sensor configuration of the data source. 14. The computer program product of claim 13 , wherein the program code instructions to provide for tuning of the subset of parameters of the localization framework for the data set comprise program code instructions to provide for tuning of the subset of parameters according to the sensor configuration of the data source. 15. A method comprising: receiving a data set from a data source; comparing the data set against data stored in a database; identifying, based on the comparison, a subset of parameters of a localization framework for the data set from among a plurality of parameters of the localization framework, wherein the subset of parameters are identified based on a predefined similarity of a sensor configuration of the data source with a sens

Assignees

Inventors

Classifications

  • Ensuring data consistency and integrity · CPC title

  • G06F16/29Primary

    Geographical information databases · CPC title

  • Database tuning (G06F16/2282 takes precedence; database performance monitoring G06F11/3409) · CPC title

  • Updates performed during online database operations; commit processing · CPC title

  • Spatial or temporal dependent retrieval, e.g. spatiotemporal queries · CPC title

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What does patent US11080311B2 cover?
Methods described herein relate to identifying critical parameters of a localization framework that may require tuning for accuracy of the localization framework based on the data source. Methods may include: receiving a data set from a data source; comparing the data set against data stored in a database; identifying, based on the comparison, a subset of parameters of a localization framework …
Who is the assignee on this patent?
Here Global Bv
What technology area does this patent fall under?
Primary CPC classification G06F16/29. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Aug 03 2021 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).