PATENT CLAIM ANALYSIS

Application Number: 16147669
Application Type: Utility
Filing Date: 2018-09
Publication Date: 2019-01
Patent Classification: ["382", "153000"]

Abstract:
Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S 900, 5910 ) obtained from a machine vision system ( 110 ), and comparison of calculated signatures to cached data within a signature localization table ( 630 ) containing previously known voxel signatures and associated geospatial positions. Signature localization tables ( 630 ) may be developed by swarms of agents ( 1000 ) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server ( 1240 ). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles ( 1400, 1402 ) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map. Differences of omission and commission between observed assets and asset characterizations with the local map cache ( 1860 ) may be reported to a central server ( 1800 ). Updates to the local signature cache ( 1852 ) and/or local map cache ( 1862 ) may be transmitted from the central server ( 1800 ) back down to vehicles within the swarm ( 1840 ).

Claim (Index 9):
The method of  claim 8 , in which the subset of the voxel signature localization table is further determined based on relative motion of the vehicle since the previous estimate of the vehicle's position.

Metadata:
- Claim Count in Document: 17.0
- Percentile: 97.0
- Lexical Diversity: 2.06422
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16147671', '15460120', '15790968', '15963833', '16058795']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.363884295091663
- 35 USC 102 Novelty (BERT): 0.5423051457523163
- Combined Prediction Score: 0.3817263801577283
- Mean Citation Score: 253.97341
- Max Citation Score: 405.97125
- Similarity Product: 252.21746849365533

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test