Autonomous Navigation Mapping for Variable Lighting Conditions
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Solution Overview
Problem
Existing autonomous machine navigation systems struggle to operate effectively in various lighting conditions, particularly outdoors during daytime, nighttime, and transitions between the two, limiting their operational flexibility and maintenance schedules.
Innovation Solution
The development of an autonomous machine navigation system that utilizes vision-based sensors and environmental lighting parameters to generate navigation maps with localization regions and buffer zones, allowing the machine to adapt its operation based on lighting conditions, ensuring consistent maintenance across different times of day.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If vision-based navigation is used for autonomous machine operation, then navigation capability is enabled, but operational reliability deteriorates in varying lighting conditions
Solution Approach 1:
The navigation map is segmented into multiple lighting condition-specific maps (daytime map, nighttime map, twilight map). Each map contains localization regions and buffer zones optimized for its specific lighting conditions. The system selectively activates appropriate maps based on current environmental lighting parameters, ensuring reliable navigation regardless of lighting variations.
Solution Approach 2:
The system dynamically transitions between different lighting condition-specific navigation maps based on real-time environmental lighting parameters. The controller monitors lighting conditions and switches between daytime, nighttime, and twilight maps accordingly, allowing the navigation system to adapt its behavior to current lighting conditions rather than using a static single map.
2Measurement precision
If lighting condition-specific navigation maps are implemented, then navigation accuracy improves, but system complexity increases
Solution Approach 1:
Multiple lighting condition-specific navigation maps are consolidated into a single unified navigation map data structure. Each lighting condition (daytime, nighttime, twilight) has its own set of localization regions and buffer zones stored within the same map framework. The controller selects and applies appropriate regions from this unified structure based on current lighting conditions, achieving multi-functionality without requiring separate physical map storage systems.
3Reliability
If localization regions and buffer zones are defined for different lighting conditions, then operational reliability improves, but computational requirements increase
Solution Approach 1:
The system extracts and stores pre-computed localization regions and buffer zones for each lighting condition during map generation. These regions are calculated in advance and stored in the navigation map data structure. During actual operation, the controller only needs to retrieve and apply the appropriate pre-computed regions based on current lighting conditions, significantly reducing real-time computational requirements while maintaining high operational reliability.
Data Source
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AI summary
Training an autonomous machine in a work region for navigation in various lighting conditions includes determining a feature detection range based on an environmental lighting parameter, determining a feature detection score for each of one or more positions in the containment zone based on the feature detection range, determining one or more localizable positions in the containment zone based on the corresponding feature detection scores, and updating the navigation map to include a localization region within the containment zone based on the one or more localizable positions. Navigation may use one or more of an uncertainty area, the localization region, and one or more buffer zones to navigate based on lighting conditions.