Multi-Sensor Fusion for VR Positioning
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Solution Overview
Problem
Existing inertial navigation systems for VR devices require a large number of sensors and high-performance processors, which are costly and consume significant power, limiting their practical application due to size, power, and cost constraints.
Innovation Solution
A data processing method for multi-sensor fusion that calculates the pose of a physical center using inertial navigation data from a minimal number of sensors, including laser and ultrasonic sensors, to reduce errors and correct inertial navigation data, thereby reducing the number of sensors and computational requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large number of sensors and high-performance processors are used to improve positioning accuracy, then measurement precision is improved, but device complexity, cost, and power consumption increase
Solution Approach 1:
The patent divides the positioning system into multiple sensor sets, each responsible for specific spatial regions. Each sensor set contains a minimal number of sensors (e.g., one laser sensor and one ultrasonic sensor) that work together to cover particular angles and directions. This segmentation allows the system to achieve comprehensive coverage without requiring every sensor to be present in every set, thereby reducing overall device complexity while maintaining positioning accuracy.
Solution Approach 2:
The patent implements a selective sensor activation strategy where only the necessary number of sensors are activated based on the current positioning requirements and environmental conditions. The system dynamically determines which sensor sets need to be active and adjusts the number of operational sensors accordingly, rather than continuously operating all sensors. This partial action approach reduces power consumption and effective device complexity while maintaining positioning precision when needed.
2Measurement precision
If more sensors are deployed to reduce positioning errors, then measurement precision is improved, but use of energy increases
Solution Approach 1:
The patent implements periodic positioning updates rather than continuous sensor operation. The system performs positioning calculations at specific time intervals or when triggered by certain conditions (e.g., when position change exceeds a threshold). Between these periodic updates, sensors remain in lower-power states or are completely deactivated. This periodic action maintains positioning accuracy by providing regular updates while dramatically reducing average power consumption compared to continuous sensor operation.
Solution Approach 2:
The system activates only the minimum necessary number of sensors required to achieve acceptable positioning accuracy for the current situation. The sensor activation is dynamic and adaptive, turning sensors on only when their contribution to reducing positioning error is needed, and turning them off when full precision is not required. This partial action principle directly addresses the contradiction by matching sensor usage to actual positioning needs, thereby reducing unnecessary energy consumption.
3Measurement precision
If sensor coverage is expanded to cover various angles, then measurement precision is improved, but device complexity and size increase
Solution Approach 1:
The patent divides the 360-degree angular coverage requirement into multiple discrete sensor sets, each covering specific angular ranges. Instead of using a single large sensor array to cover all angles simultaneously, the system segments the coverage task across multiple smaller sensor sets positioned at different orientations. Each sensor set contains minimal sensors (e.g., one laser and one ultrasonic sensor) that cover their assigned angular sector, achieving comprehensive angular coverage through spatial segmentation rather than through a single bulky sensor array.
Solution Approach 2:
The patent transitions from a two-dimensional planar sensor arrangement to a three-dimensional spatial configuration. Sensor sets are positioned at different heights, angles, and locations in 3D space, allowing the system to achieve comprehensive angular coverage by exploiting the third dimension. This vertical and spatial distribution of minimal sensor sets replaces what would otherwise require a large two-dimensional sensor array, thereby reducing the footprint and volume of the positioner while maintaining full angular coverage capability.
Data Source
AI summary
Provided are a data processing method for multi-sensor fusion, a positioning apparatus and a VR device. The method includes: calculating a pose of a physical center by using data of at least one sensor set in a first positioning period; obtaining the predicted pose of the physical center according to an inertial navigation of the pose of the physical center; calculating a three-dimensional coordinate pose of each sensor set in a second positioning period; calculating, based on the three-dimensional coordinate pose, third inertial navigation data of each sensor set in the second positioning period; obtaining the converted poses of the physical center respectively through the third inertial navigation data and a pose relationship between each sensor and the physical center; and obtaining the predicted pose of each sensor set based on the converted poses of the physical center.