Multi-Camera System Dynamic Stereo Pair Selection
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Solution Overview
Problem
Conventional multi-camera systems for vision-based navigation are limited by predefined stereocamera pairs, which restrict monitored regions to overlapping areas, leading to reduced coverage and increased costs due to the need for high-performance processors and extensive data processing.
Innovation Solution
A multi-camera system that dynamically selects camera subsets based on robot kinematics and environment, allowing for real-time image processing and 3D map creation, with cameras sharing a common processor and storage, reducing processing load and costs while expanding monitored regions beyond traditional overlapping areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If predefined stereocamera pairs are used for vision-based navigation, then measurement precision is maintained, but monitored region coverage is reduced and device complexity increases
Solution Approach 1:
The system dynamically selects and forms stereocamera pairs from a larger plurality of cameras based on current navigation needs and environmental conditions. Instead of using fixed predefined pairs, the system can reconfigure which cameras work together as a stereopair, allowing the monitored region to expand beyond what any single fixed pair could cover while maintaining depth measurement precision through dynamic reconfiguration.
Solution Approach 2:
The system divides the overall monitoring task into segments handled by different camera pairs at different times. By having multiple cameras that can be paired dynamically, the system segments the coverage area across multiple camera fields of view, with each stereopair responsible for a specific region while the system as a whole achieves comprehensive coverage through temporal and spatial segmentation.
2Area of stationary object
If multiple cameras are used to expand monitored regions, then coverage is increased, but processing load and costs increase
Solution Approach 1:
The system dynamically activates only the necessary subset of cameras for current navigation tasks rather than continuously processing data from all cameras. By forming stereocamera pairs on-demand based on robot kinematics and environmental context, the system processes only relevant image streams, significantly reducing computational load while maintaining expanded coverage capability when needed.
Solution Approach 2:
The system applies different processing quality and intensity to different camera subsets based on local needs. Cameras that are currently forming an active stereopair receive full processing attention for depth measurement, while other cameras may have reduced processing or be temporarily inactive. This local quality differentiation allows expanded coverage without proportionally increasing overall processing load.
3Adaptability or versatility
If predefined stereocamera pairs are used, then processing is simplified, but adaptability to different navigation scenarios is reduced
Solution Approach 1:
The system uses dynamic camera selection based on robot kinematics (velocity, acceleration, orientation) and environmental conditions to automatically determine which cameras should form stereopairs for current navigation scenarios. This dynamic adaptation allows the system to handle diverse scenarios such as forward flight, lateral movement, and vertical navigation by selecting appropriate camera subsets without requiring manual reconfiguration or complex hardware changes.
Data Source
AI summary
A method for operating a system including a plurality of cameras, the method including: selecting a subset of the cameras, determining a subset of pixels captured by the camera subset, determining a pixel depth associated with each pixel of the pixel subset, and controlling system operation based on the pixel depth.