Multi-Time-Zone Map Selection for Robust Mobile Localization
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Solution Overview
Problem
Existing localization systems face challenges in accurately predicting the influence of environmental information on map accuracy, leading to potential decreases in localization accuracy.
Innovation Solution
A localization system that acquires map data across different time zones, creates synthetic map candidates by combining maps, calculates performance values for these candidates, and selects the best candidate for localization based on predetermined criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single map is selected for localization based on environmental information, then the localization process is simple, but the localization accuracy decreases when environmental conditions change
Solution Approach 1:
The patent divides the localization system into multiple synthetic map candidates, each representing different environmental conditions. Instead of using a single map, the system segments the environmental space into multiple representable maps and selects the most appropriate one based on current conditions, thereby maintaining both operational simplicity and high localization accuracy.
Solution Approach 2:
The patent implements a dynamic map selection mechanism that adapts to changing environmental conditions. The system dynamically determines which synthetic map candidate best matches current environmental information, allowing the localization process to remain simple while automatically adjusting to maintain high accuracy under varying conditions.
2Measurement precision
If multiple synthetic map candidates are created and evaluated, then the localization accuracy improves, but the system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-generating multiple synthetic map candidates covering different environmental conditions before actual localization is needed. This preparation work is done in advance, so when localization is required, the system only needs to evaluate and select from pre-prepared candidates, reducing the complexity of real-time processing while maintaining high accuracy.
Solution Approach 2:
The patent implements a feedback mechanism where the system evaluates each synthetic map candidate against current environmental information and selects the best match. This feedback-driven selection process automates the complexity management, allowing the system to handle multiple map candidates without proportionally increasing operational complexity, as the selection is performed algorithmically based on environmental feedback.
3Adaptability or versatility
If map data from multiple time zones is acquired and combined, then the adaptability to environmental changes improves, but the data processing complexity increases
Solution Approach 1:
The patent segments map data from multiple time zones into distinct synthetic map candidates, each representing specific environmental conditions. This segmentation allows the system to handle diverse temporal data in manageable units, improving adaptability to environmental changes while controlling processing complexity through structured organization of multi-temporal data.
Data Source
AI summary
A localization system includes: a first data acquisition unit that acquires map data for map creation in a plurality of different time zones; a candidate creation unit that creates the maps based on the map data acquired by the first data acquisition unit, and combines the created maps to create a plurality of synthetic map candidates; a performance calculation unit that calculates a performance value of each of the synthetic map candidates created by the candidate creation unit; a candidate selection unit that selects one synthetic map candidate from among the plurality of synthetic map candidates based on the performance value of the synthetic map candidate calculated by the performance calculation unit; and a localization unit that performs localization of a mobile body based on the synthetic map candidate selected by the candidate selection unit.