VR Play Area Auto-Configuration With Obstruction Awareness
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Solution Overview
Problem
Current virtual reality (VR) headsets require manual configuration of a play area, which can result in irregular boundaries and fail to maximize the available space for movement, and lack depth sensing capabilities for accurate obstruction detection, posing risks of physical harm during room-scale experiences.
Innovation Solution
The system uses LiDAR and optical sensors to automatically configure a VR play area by performing depth sensing in all directions, augmenting with imaging data to map the environment, identify horizontal planes, and dynamically adjust the play area to ensure maximum space and safety, incorporating features like center positioning and obstruction detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If manual configuration of play area is used, then user can define boundary, but the boundaries become irregular and available space is not maximized
Solution Approach 1:
The system performs automatic configuration of the play area boundary without requiring manual user input. The HMD automatically maps the environment using depth sensing and camera data, identifies the floor plane and obstructions, and computes the optimal convex play area boundary that maximizes available space while ensuring safety.
Solution Approach 2:
The system transforms the play area boundary from an irregular manually-drawn shape to a regular convex shape by changing the geometric parameters. This is achieved by computing the convex hull of the detected environment, which mathematically guarantees the largest possible area while maintaining a regular boundary form.
2Measurement precision
If depth sensing (LiDAR) is not used, then device complexity is reduced, but accurate obstruction detection capability is insufficient
Solution Approach 1:
The system makes the HMD's cameras perform multiple functions: they not only track the user's head position and orientation but also capture environmental images for play area mapping and obstruction detection. This multi-functionality allows the system to achieve accurate obstruction detection without adding dedicated depth sensing hardware.
Solution Approach 2:
The system uses computer vision algorithms as an intermediary to extract depth and obstruction information from 2D camera images. By applying image processing and feature detection techniques, the system can infer three-dimensional spatial relationships and obstruction locations without direct depth sensing measurements.
3Extent of automation
If automatic configuration is implemented, then play area is maximized and safety is improved, but device complexity increases
Solution Approach 1:
The system combines existing HMD components (cameras, inertial sensors, processors) that were already present for other functions into an integrated automatic play area configuration system. By merging these existing capabilities, the system achieves high automation without significantly increasing overall device complexity.
Solution Approach 2:
The system performs automatic play area configuration as a preliminary step before the user begins VR gameplay. By completing the environment mapping, boundary computation, and obstruction identification in advance, the system enables fully automated operation during the actual gaming session without requiring real-time complex processing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method enables a more efficient, safe, and immersive VR experience by maximizing the play area and reducing the risk of physical harm through automated boundary configuration and real-time obstruction awareness.
Implementation Method 1
The HMD performs time-of-flight/LiDAR/depth sensing measurements in the vicinity of the user in all directions
Implementation Method 2
The HMD performs time-of-flight/LiDAR/depth sensing measurements in the vicinity of the user in all directions
Implementation Method 3
The HMD cameras use sophisticated computer vision algorithms to determine and track how optical feature points in the environment move relative to the HMD
Data Source
AI summary
A virtual reality play area is defined. Movement of an object in the vicinity of the play area may then be detected. Based on the movement of the object, it may be determined whether the object is projected to enter the play area. If the object is projected to enter the play area, a representation of the object is generated for display to the user.