PATENT CLAIM ANALYSIS

Application Number: 15924025
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["345", "419000"]

Abstract:
A wearable device is configured with a one-dimensional depth sensor (e.g., a LIDAR system) that scans a physical environment, in which the wearable device and depth sensor generate a point cloud structure using scanned points of the physical environment to develop blueprints for a negative space of the environment. The negative space includes permanent structures (e.g., walls and floors), in which the blueprints distinguish permanent structures from temporary objects. The depth sensor is affixed in a static position on the wearable device and passively scans a room according to the gaze direction of the user. Over a period of days, weeks, months, or years the blueprint continues to supplement the point cloud structure and update points therein. Thus, as the user continues to navigate the physical environment, over time, the point cloud data structure develops an accurate blueprint of the environment.

Claim (Index 15):
One or more hardware-based computer-readable memory devices storing instructions which, when executed by one or more processors disposed in a computing device, cause the computing device to:\n periodically receive point data directly or indirectly from a depth sensor; timestamp each point or group of points in the point data; build a map of negative space representing non-transient structures using the point data; discard the point data which represents transient structures; and update the map or a point cloud structure as point data is periodically received at temporally different times, in which updating the map or the point cloud structure includes at least one of:\n i) increasing a count associated with a point when the point in subsequent point data corresponds to a point in previous point data; and \n ii) replacing a point in previous point data with a point in subsequent point data.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 90.0
- Lexical Diversity: 2.0
- Patent Class: 345.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15923761', '13892987', '14875065', '14697109', '12900866']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6400648576719217
- 35 USC 102 Novelty (BERT): 0.4814103603638334
- Combined Prediction Score: 0.6241994079411128
- Mean Citation Score: 163.54678200000004
- Max Citation Score: 199.25377
- Similarity Product: 151.21084494008426

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