Smartphone Sensor Fusion for Indoor Navigation Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing navigation technologies for indoor spaces, particularly for individuals with visual disabilities, face challenges such as the need for detailed maps, infrastructure installation, and handling uncertainties in user and path positions, limiting their applicability and accuracy.
Innovation Solution
A self-sufficient navigation system that uses location sensors to record paths and uncertainties, allowing for the piecing together of existing paths to find optimal routes, hypothesizing connectivity between untraversed points, and dynamically updating paths based on user movement, without requiring pre-created maps or infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed maps and infrastructure (beacons/tags) are installed for indoor navigation, then navigation accuracy is improved, but device complexity and implementation cost increase significantly
Solution Approach 1:
The system uses the smartphone's existing sensors (accelerometer, gyroscope, magnetometer, barometer) to perform self-localization without requiring external infrastructure. The device serves itself by using its own sensors to track position and orientation through inertial navigation and sensor fusion algorithms.
Solution Approach 2:
The patent extracts the navigation functionality from dependency on external infrastructure (maps, beacons, tags) and implements it using only the smartphone's built-in sensors. This removes the need for complex external systems while maintaining navigation capability.
2Measurement precision
If pre-created detailed maps are used for route planning, then route accuracy is improved, but adaptability to unfamiliar or dynamic environments deteriorates
Solution Approach 1:
The system dynamically adapts to the current environment by continuously processing sensor data in real-time. Instead of relying on static pre-created maps, the navigation adjusts to unfamiliar or changing environments by using live sensor measurements and probabilistic position estimation.
Solution Approach 2:
The system changes its operational parameters by switching from map-based navigation to sensor-based inertial navigation. This allows the system to adapt to different environments by adjusting its localization method based on available information and environmental conditions.
3Productivity
If traditional route planning systems use accurate maps, then route optimization is improved, but applicability to spaces without maps deteriorates
Solution Approach 1:
The patent extracts the essential navigation function from map dependency and implements it using sensor-based position tracking. This allows route planning and optimization to occur in mapless environments by using probabilistic position estimates derived from sensor fusion.
Solution Approach 2:
The system introduces probabilistic position estimation as an intermediary between sensor data and route planning. This mediator allows the route planning algorithm to function without direct map input by working with probability distributions of possible positions.
4Measurement precision
If GPS is used for position tracking, then position accuracy in outdoor environments is improved, but usability indoors deteriorates due to lack of GPS coverage
Solution Approach 1:
The system changes its localization approach by switching from GPS-based absolute positioning to sensor-based relative positioning. This parameter change enables continuous operation both indoors and outdoors by adapting to the availability of different positioning technologies.
Solution Approach 2:
The patent segments the navigation system into multiple independent components (inertial navigation, sensor fusion, probabilistic positioning) that can operate independently of GPS. This segmentation allows the system to function in environments where GPS is unavailable.
Data Source
AI summary
A method provides navigation assistance to a user by tracking the user's position. By detecting similar features, the accuracy of the position measurement of the user is improved, making use of a priori frequencies that various feature types exist in the area. The method provides techniques for planning a route using the tracking information and is able to explore previously-untraveled paths in response to a setting in the search process. The navigation information can be saved or retrieved from a database so that users may share the data obtained during navigating an unfamiliar area.