Adaptive Virtual Object Placement Through Real-World Scanning
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Solution Overview
Problem
Existing augmented reality systems struggle to seamlessly integrate virtual objects into real-world environments, leading to a disjointed user experience.
Innovation Solution
A computer-implemented method involving scanning the real-world environment, determining suitable locations based on predefined conditions, and scaling virtual objects to fit the scanned environment, using techniques like SLAM and LIDAR to ensure accurate placement and alignment with real-world features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If virtual objects are placed in augmented reality environments using fixed positioning methods, then the placement process is simple, but the user immersion and realism are reduced
Solution Approach 1:
The system dynamically adjusts virtual object placement based on real-time environmental scanning and recognition. Instead of fixed positioning, the system continuously adapts the position, orientation, and scale of virtual objects to match the actual physical environment detected through cameras and sensors, creating a seamless augmented reality experience.
Solution Approach 2:
The system performs automatic environmental scanning, feature detection, and virtual object positioning without requiring manual intervention. The augmented reality system self-adjusts by comparing detected real-world features with virtual object parameters, automatically determining optimal placement locations that enhance immersion while maintaining operational simplicity.
2Manufacturing precision
If virtual objects are scaled to fit real-world environments, then the realism and immersion are improved, but the positioning precision requirements increase
Solution Approach 1:
The system dynamically changes multiple parameters including scale, position, and orientation of virtual objects based on environmental feedback. By adjusting these parameters in response to detected real-world features and spatial constraints, the system achieves precise positioning while maintaining flexibility to adapt to various environments.
Solution Approach 2:
The system uses continuous feedback from environmental scanning and feature detection to adjust virtual object placement. The detected real-world geometry and spatial relationships provide feedback that guides the scaling and positioning of virtual objects, ensuring precision while adapting to different environmental contexts.
3Measurement precision
If environmental scanning is performed continuously, then the accuracy of virtual object placement is improved, but the processing time and energy consumption increase
Solution Approach 1:
The system performs environmental scanning periodically or at key moments rather than continuously. Scanning is triggered by specific events such as user entry into a new space, changes in device orientation, or predetermined intervals, balancing detection accuracy with reduced processing time and energy consumption.
Solution Approach 2:
The system performs preliminary environmental scanning and feature detection before virtual object placement. By pre-processing the environment data and identifying key features in advance, the system reduces the time required for actual placement operations while maintaining high positioning accuracy.
Data Source
AI summary
A computer-implemented method includes selecting a virtual object to be positioned in a mixed-reality environment, the virtual object having one or more conditions relating to the positioning of the virtual object, scanning a real-world part of the mixed-reality environment, determining a location to position the virtual object based on the scan, wherein the location satisfies the one or more conditions, scaling the virtual object based on the location, and positioning the virtual object in the mixed-reality environment at the determined location.