PATENT CLAIM ANALYSIS

Application Number: 16014311
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-10
Patent Classification: ["382", "103000"]

Abstract:
Methods, apparatus, systems, and computer-readable media are provided for delegating object type and/or pose detection to a plurality of “targeted object recognition modules.” In some implementations, a method may be provided that includes: operating an object recognition client to facilitate object recognition for a robot; receiving, by the object recognition client, sensor data indicative of an observed object in an environment; providing, by the object recognition client, to each of a plurality of remotely-hosted targeted object recognition modules, data indicative of the observed object; receiving, by the object recognition client, from one or more of the plurality of targeted object recognition modules, one or more inferences about an object type or pose of the observed object; and determining, by the object recognition client, information about the observed object, such as its object type and/or pose, based on the one or more inferences.

Claim (Index 4):
The method of  claim 3 , further comprising rendering two or more canonical objects based on the two or more canonical models, wherein the comparing includes comparing the two or more canonical objects with the at least some of the sensor data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.47761
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15230412', '15640914', '14874419', '15227612', '15592849']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2696901884213864
- 35 USC 102 Novelty (BERT): 0.5182898373490662
- Combined Prediction Score: 0.2945501533141544
- Mean Citation Score: 181.86008400000003
- Max Citation Score: 289.8638
- Similarity Product: 204.79369691338545

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