Hybrid Inertial-Visual Tracking System for 6DOF Positioning
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Solution Overview
Problem
Existing tracking systems face challenges in accurately tracking unpredictable and erratic movements of objects, especially at distances, due to resource-intensive image processing and inaccuracy issues, particularly when multiple objects are being tracked simultaneously or under poor lighting conditions.
Innovation Solution
A tracking system utilizing a combination of image tracking and inertial measurements, where infrared light sources attached to objects are detected by multiple cameras, with inertial measurement units providing angular orientation and acceleration data, and a Kalman filter-based state machine generating precise position and orientation data, allowing for real-time tracking of multiple objects with high accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual imaging systems are used to track object movement, then tracking capability is provided, but processing becomes resource intensive and tracking response rate slows down
Solution Approach 1:
The patent combines visual imaging systems with inertial measurement units (IMUs) to create a hybrid tracking system. The IMU provides rapid angular orientation and acceleration data that complements camera-based position tracking, enabling the system to maintain high response rates while improving tracking reliability through multi-sensor fusion.
Solution Approach 2:
The tracking system integrates multiple sensor types (cameras and IMUs) that can operate independently or together. The IMU subsystem provides tracking functionality even when visual sensors are unavailable or overwhelmed, making the system universally applicable to various tracking scenarios without sacrificing response rate.
2Length of stationary object
If sensors are positioned further away from the object being tracked, then tracking range is extended, but inaccuracy increases
Solution Approach 1:
By merging camera-based visual tracking with IMU-based inertial tracking, the system achieves extended tracking range while maintaining accuracy. The IMU compensates for the reduced precision of distant visual sensors by providing local motion measurements that remain accurate regardless of distance.
Solution Approach 2:
The IMU acts as an intermediary sensor that bridges the gap between distant visual sensors and the tracked object. It provides intermediate motion data that maintains tracking accuracy even when the primary visual sensors are positioned far from the object.
3Adaptability or versatility
If multiple objects are tracked simultaneously, then system versatility is improved, but processing complexity increases
Solution Approach 1:
The patent segments the tracking system into independent sensor modules (cameras and IMUs) that can process data for multiple objects simultaneously. Each sensor type processes information independently before fusion, reducing overall processing complexity while maintaining the ability to track multiple objects.
Solution Approach 2:
The hybrid architecture merges data from multiple sensor types in a centralized fusion process that efficiently handles multiple objects. The IMU data provides consistent reference frames that simplify the processing of multiple object trajectories compared to using only visual sensors.
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
The system achieves accurate six-degrees-of-freedom tracking with high response rates, capable of handling multiple objects from varying distances and angles, even in challenging lighting conditions, by integrating image and inertial data for robust position and orientation determination.
Implementation Method 1
inertial measurement units providing angular orientation and acceleration data
Implementation Method 2
infrared light sources attached to objects are detected by multiple cameras
Data Source
AI summary
Systems and methods are provided for tracking at least position and angular orientation. The system comprises a computing device in communication with at least two cameras, wherein each of the cameras are able to capture images of one or more light sources attached to an object. A receiver is in communication with the computing device, wherein the receiver is able to receive at least angular orientation data associated with the object. The computing device determines the object's position by comparing images of the light sources and generates an output comprising the position and angular orientation of the object.