Localization Map Weight Adjustment for Mobile Positioning
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Solution Overview
Problem
The risk of incorrect localization in mobile devices due to similar regions in a localization map, where features are similar and can lead to incorrect determination of the device's position.
Innovation Solution
A method where a map server modifies the localization map by adjusting the weights of similar features, reducing their impact and increasing the relative importance of non-similar features to enhance localization accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the localization map contains regions with similar features, then the map can represent more diverse environments, but the risk of incorrect localization increases
Solution Approach 1:
The patent applies local quality by adjusting the weights of features locally within the localization map. Specifically, when similar regions are detected, the weights of features in those regions are modified to reduce similarity, while features in unique regions maintain their original weights. This localized adjustment resolves the contradiction by preserving environmental diversity in the map while ensuring accurate differentiation between similar regions for reliable localization.
2Measurement precision
If feature weights are adjusted to reduce similarity, then localization accuracy improves, but computational complexity increases
Solution Approach 1:
The patent implements preliminary action by pre-processing the localization map to identify and adjust weights of similar features before actual localization operations. The map server performs weight adjustment in advance based on feature similarity analysis, so that when mobile devices perform localization, they work with pre-optimized map data. This approach improves localization accuracy while reducing real-time computational complexity for mobile devices.
3Quantity of substance
If all features are used for localization, then more information is available, but the impact of similar features causes incorrect determination
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the weights of features based on their similarity to other features in the map. Instead of using all features uniformly, the system modifies the weight parameter of each feature according to its uniqueness. Features in similar regions have their weights reduced, while unique features maintain higher weights. This selective weighting resolves the contradiction by preserving rich feature information while ensuring reliable position determination through differentiated feature importance.
Data Source
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AI summary
It is provided a method for supporting localisation of a mobile device based on a localisation map comprising a number of features, wherein each feature comprises location data and geometric characteristics of the feature. The method comprises: determining a local localisation map based on a location of the mobile device; finding, in the local localisation map, at least a first region and a second region which comprise similar features; modifying the local localisation map to reduce similarity between the first region and the second region; and transmitting the modified local localisation map to the mobile device.