Edge-Based 3D Location Cells for Time-Valid Mapping
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Solution Overview
Problem
Existing location systems are based on outdated geocoding principles that do not inherently include altitude and time, making them inadequate for dynamic, high-definition mapping required by autonomous machines, and central platforms are unable to efficiently serve a large number of autonomous objects due to latency and privacy concerns.
Innovation Solution
TensorLocation, a framework utilizing TensorCells, which are semantically segmented 2D or 3D spaces with validity intervals, executed by edge computing and federated learning, and secured by distributed ledger technology, enabling low-latency, privacy-preserving, and context-aware location services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If location systems use traditional geocoding principles, then the system structure is simple, but the system cannot provide time-valid location information with altitude for autonomous machines
Solution Approach 1:
The patent segments the environment into a three-dimensional grid of cells, where each cell represents a specific spatial volume with defined boundaries. This segmentation allows the system to track objects within discrete spatial units, enabling precise location information including altitude, while maintaining a structured and manageable system architecture that can be implemented through software algorithms.
Solution Approach 2:
The patent transitions from traditional two-dimensional geocoding to a three-dimensional cell-based system by adding the altitude dimension. Each cell is defined by spatial coordinates (x, y, z) and temporal validity intervals, creating a four-dimensional space-time framework that provides comprehensive location information for autonomous machines while preserving system simplicity through regular grid structures.
2Loss of information
If a central platform serves a large number of autonomous objects, then comprehensive location information can be provided, but latency and privacy concerns increase
Solution Approach 1:
The patent implements a decentralized architecture where autonomous objects independently determine their own location by identifying which cell they occupy and calculating their coordinates within that cell. Each object maintains its own position data and can provide location information without querying a central platform, eliminating latency while preserving complete location information through self-reported data.
3Loss of information
If a central platform serves a large number of autonomous objects, then comprehensive location information can be provided, but privacy concerns increase
Solution Approach 1:
The patent extracts the central platform from the location information system, removing it as a point of data collection and control. Instead, autonomous objects independently manage and report their own location data, eliminating the privacy risks associated with centralized data aggregation while maintaining complete and accurate location information through distributed peer-to-peer communication.
4Ease of manufacture
If traditional geocoding is used, then the system is easy to implement, but it cannot support dynamic mapping requirements for autonomous machines
Solution Approach 1:
The patent implements a dynamic cell-based mapping system where the environment is divided into discrete cells that can be efficiently queried and updated. The system dynamically determines which cells contain autonomous objects and tracks their movement between cells over time, enabling flexible adaptation to changing spatial configurations while maintaining implementation simplicity through standardized cell structures and algorithms.
Data Source
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AI summary
A computer-implemented method can provide time-valid location-based information. The method comprises: for an environment, defining a plurality of cells, each cell comprising: a respective location with a range based on a geographical extent of the respective cell within the environment; a respective predetermined validity-time-interval; respective semantic-location-data relevant to the respective location; respective executable code instructions configured to operate on the respective semantic-location-data to enable determination of respective time-valid location-based information upon execution of the respective code instructions by a first edge computing apparatus proximal to the respective location. The respective time-valid location-based information is valid within the respective predetermined validity-time-interval.