Quasi-random XR Item Placement via Spatial Mapping Mesh
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Solution Overview
Problem
Current XR technologies fail to create immersive experiences by allowing virtual characters to interact naturally with real elements in mixed reality spaces, as they are often positioned arbitrarily and do not account for the spatial relationships and accessibility of real-world objects, leading to unrealistic interactions and navigation challenges.
Innovation Solution
The method involves predefining activity zones and virtual item placement using spatial mapping meshes to determine accessible and natural interaction points within the XR space, ensuring virtual characters can engage in believable activities and navigate between real-world surfaces by generating quasi-random spawn positions and collision analyses to optimize accessibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If virtual characters are positioned arbitrarily in XR space, then device complexity is reduced, but realism and natural interaction are worsened
Solution Approach 1:
The system performs preliminary spatial mapping and pre-defines activity zones before virtual characters are placed in the XR space. By analyzing the physical environment in advance and identifying suitable interaction zones, the system ensures that virtual characters are subsequently positioned in realistic locations that naturally interact with real-world elements, rather than placing them arbitrarily.
2Productivity
If virtual items are placed at random positions, then placement speed is improved, but accessibility and user engagement are worsened
Solution Approach 1:
The system divides the XR space into distinct activity zones with different qualities and characteristics based on their proximity to real-world elements and their suitability for various interactions. Virtual items are then placed in zones with appropriate local qualities that match their function and ensure accessibility, rather than using uniform random placement throughout the entire space.
3Manufacturing precision
If collision analysis is performed for all positions, then placement precision is improved, but computational efficiency is worsened
Solution Approach 1:
The system segments the continuous XR space into discrete activity zones based on spatial mapping data and real-world element boundaries. Collision analysis is then performed only within these segmented zones rather than across the entire space, significantly reducing computational resources while maintaining placement precision within each zone.
4Reliability
If activity zones are predefined using spatial mapping, then interaction realism is improved, but system complexity is worsened
Solution Approach 1:
The spatial mapping system automatically identifies and defines activity zones by analyzing the physical environment and determining suitable interaction regions, without requiring manual configuration or complex programming. The system serves itself by using its own mapping data to generate placement zones, reducing the need for additional complexity in the overall system architecture.
Data Source
AI summary
A method for quasi-random placement of a virtual item in an XR space includes: accessing a previously generated spatial mapping mesh (SMM) of the XR space; compiling a record from the SMM of open spaces between surfaces of physical elements in the XR space, with corresponding positions and dimensions; selecting from the open spaces: a spawn position for a virtual character, and a random set of other positions, filtering the random set to form a subset. The method then performs a collision analysis to assign a score to each position in the subset partly based on accessibility to that position for the virtual character beginning from the spawn position; and places the virtual item at a position in the subset having a score as high or higher than all other positions in the subset. The method is carried out before user interaction with any virtual element in the XR space.