Scene-Perception Group Guidance for Collision-Free VR Exhibit Viewing
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Solution Overview
Problem
Existing group guidance techniques in virtual reality require manual selection of positions for each team member, leading to inefficiencies due to the need for collision avoidance and optimal viewing positions, resulting in increased guide burden and reduced navigation efficiency.
Innovation Solution
An automated formation group guidance method based on scene perception that determines initial and optimized visit positions using social distance thresholds and queue lengths, optimizing view quality and minimizing position deflection angles through a matching strategy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual position selection is used for each team member, then collision avoidance and optimal viewing positions can be ensured, but guide burden increases and navigation efficiency decreases
Solution Approach 1:
The system enables self-service by automatically generating collision-free visit position queues and optimizing viewing positions without manual guide intervention. The automated formation group guidance method calculates positions based on social distance thresholds and queue lengths, allowing the system to serve itself rather than requiring continuous guide input.
Solution Approach 2:
The system performs preliminary action by pre-calculating and optimizing visit position queues before navigation begins. The method determines initial visit position queues based on queue lengths and social distance thresholds, then optimizes these positions in advance to ensure collision avoidance and optimal viewing angles, eliminating the need for real-time manual adjustments.
2Manufacturing precision
If manual position selection is used for each team member, then optimal viewing positions can be ensured, but operation complexity increases
Solution Approach 1:
The system replaces the mechanical manual selection process with an automated computational system. Instead of guides manually selecting positions, the method uses algorithms to calculate initial visit position queues, optimize viewing positions based on quality metrics, and generate navigation instructions automatically, substituting human operation with automated processing.
Solution Approach 2:
The system changes parameters by automatically adjusting visit positions based on optimization criteria such as viewing angle quality, social distance thresholds, and queue lengths. The method modifies position parameters dynamically to achieve optimal viewing conditions without requiring manual intervention, transforming the operation from complex manual selection to automated parameter optimization.
3Productivity
If automated position generation is used, then navigation efficiency improves, but view quality may decrease
Solution Approach 1:
The system performs preliminary optimization of viewing positions before navigation begins. The method calculates initial visit position queues and then optimizes each position to maximize view quality metrics such as viewing angle and distance to exhibits. This pre-optimization ensures that automated position generation achieves both high navigation efficiency and excellent view quality simultaneously.
Solution Approach 2:
The system changes position parameters through automated optimization that adjusts visit positions based on quality criteria. The method modifies coordinates, angles, and distances to achieve optimal viewing conditions while maintaining automated generation, thereby improving view quality without sacrificing navigation efficiency.
Data Source
AI summary
Embodiments of this disclosure propose an automated formation group guidance method based on scene perception. One implementation of this method includes: in response to receiving jump position information, determining whether a jump position corresponding to the jump position information is within any exhibit area; in response to determining that the jump position is within any exhibit area, based on a social distance threshold and a queue length, determining an initial visit position queue corresponding to a target exhibit; optimizing each initial visit position to obtain an optimized visit position queue; based on a preset matching strategy, matching the optimized visit position queue and a current visitor position information queue to obtain a target visitor position information queue, for guiding each visitor to perform position jumps and browse target exhibits.