Neighboring Map Data Sharing for Precise Multi-Device Alignment
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Solution Overview
Problem
Current methods for enabling multiple devices to align their 6-DoF coordinates in three-dimensional space face challenges such as the need for external sensors, high setup costs, slow data transmission, and loss of local map data when sharing common maps, limiting spontaneity and reliability in scenarios like hologram sharing and robot coordination.
Innovation Solution
A computing device and method that transmit a relevant subset of map data, called a neighborhood, to enable mutual spatial understanding among display devices, allowing them to display shared holograms at the same location by incorporating neighboring map data into existing map data, without requiring external sensors or extensive data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If external sensors are used to enable multiple devices to align their 6-DoF coordinates, then measurement precision is improved, but device complexity and setup cost increase
Solution Approach 1:
The patent uses shared map data as an intermediary to enable coordinate alignment between devices. Instead of direct sensor-to-sensor communication or complex external sensor systems, each device independently maps its environment and shares map data with others. The map serves as a common reference frame that allows devices to align their coordinates without requiring direct sensor coordination or complex external infrastructure.
2Measurement precision
If complete map data is transmitted between devices to enable spatial understanding, then measurement precision is improved, but loss of time increases due to extensive data transmission
Solution Approach 1:
The patent extracts and transmits only the relevant portions of map data (neighborhoods) rather than complete maps. When a device needs spatial understanding of a particular location, it requests and receives only the map neighborhood data for that specific area. This extraction approach provides sufficient spatial precision for the task while dramatically reducing data transmission time and bandwidth requirements compared to sharing entire maps.
3Reliability
If complete map data is shared between devices, then reliability of spatial understanding is improved, but loss of information occurs when local map data is lost during transmission
Solution Approach 1:
The patent segments the complete map into smaller neighborhood units. Each device maintains its own local map data and can share specific neighborhoods with other devices. This segmentation means that if data is lost during transmission, only the specific neighborhood being transmitted is affected, not the entire map. Devices can continue to operate with their local map data while selectively sharing relevant neighborhoods, maintaining overall system reliability while minimizing information loss.
Data Source
AI summary
A computing device and method are provided for transmitting a relevant subset of map data, called a neighborhood, to enable mutual spatial understanding by multiple display devices around a target virtual location to display a shared hologram in the same exact location in the physical environment at the same moment in time. The computing device may comprise a processor, a memory operatively coupled to the processor, and an anchor transfer program stored in the memory and executed by the processor.