Vehicle Obstacle Detection Using Multi-Directional Shadow Imaging
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Solution Overview
Problem
Existing imaging systems struggle to detect and identify obstacles that have light-emanating properties identical or similar to their background, making it difficult to distinguish between objects that blend into their surroundings and those that pose a hazard, especially in low-visibility conditions.
Innovation Solution
The Object Detection and Identification (ODI) system employs active scene illumination to generate and analyze shadows cast by objects, using a combination of illuminators and imagers spaced apart to characterize objects as obstacles or non-obstacles through gated imaging techniques and machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If passive imaging systems are used to detect objects, then the system complexity is reduced, but the ability to detect objects with identical light characteristics to background is severely limited
Solution Approach 1:
The system performs preliminary scene illumination before detection by activating illuminators to cast light on the scene and generate shadows. This preliminary action creates the shadow patterns that enable subsequent detection of objects with identical light characteristics to their background, resolving the contradiction by adding a preparatory step that enhances detection capability without requiring complex passive imaging systems.
Solution Approach 2:
The system introduces shadows as an intermediary element between the illuminator and the object detection process. By analyzing shadow patterns cast by objects, the system can detect objects that would otherwise be indistinguishable from their background, effectively using shadows as a mediating mechanism to overcome the limitation of passive imaging systems.
2Measurement precision
If active scene illumination is used to generate shadows for object detection, then object detection precision is improved, but energy consumption increases
Solution Approach 1:
The system employs periodic illumination by activating and deactivating illuminators in timed sequences rather than continuous operation. This periodic action allows the system to capture shadow patterns at specific moments while reducing overall energy consumption, resolving the contradiction between detection precision and energy usage by optimizing the timing and duration of illumination events.
Solution Approach 2:
The system applies partial illumination by activating only specific illuminators or illuminating only certain regions of the scene rather than illuminating the entire scene continuously. This partial action approach maintains sufficient detection precision for critical areas while reducing total energy consumption, balancing the trade-off between detection capability and energy efficiency.
3Measurement precision
If multiple illuminators and imagers are deployed to analyze shadows from different directions, then object characterization accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the illumination and detection functions by deploying multiple illuminators and imagers at different locations and orientations. Each illuminator-imager pair captures shadow information from a specific direction, and the system integrates these segmented measurements to achieve comprehensive object characterization, resolving the contradiction by dividing the complex task into manageable directional components.
Solution Approach 2:
The system adds spatial dimensionality by positioning illuminators and imagers at different locations and angles throughout the scene. This multi-dimensional arrangement enables the system to capture shadow patterns from multiple perspectives, significantly improving object characterization accuracy while distributing the complexity across multiple simpler sensor positions rather than requiring a single complex system.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively detects and identifies obstacles that blend into their background by increasing contrast through shadow analysis, enhancing visibility and safety in various weather and lighting conditions, including nighttime and adverse weather.
Implementation Method 1
a plurality of illuminators... arranged at different locations of the platform... for illuminating a scene
Implementation Method 2
light may be reflected from objects located within that scene and detected by a light sensor of the active imaging system to produce 'reflection-based' image data
Implementation Method 3
The system employs active scene illumination to generate and analyze shadows cast by objects
Data Source
AI summary
Embodiments pertain to a system that can be employed or that is included in a platform for detecting an obstacle to the platform in a scene. The system comprises, in an embodiment, a plurality of illuminators arranged at different locations of the platform; at least one imager; a processor; and a memory configured to store data and software code. The software code is executable by the processor to perform the following: illuminating the scene from at least two different directions by the plurality of illuminators; acquiring, by the at least one imager, a plurality of images of the illuminated scene; comparing at least one image of the scene illuminated from a first direction with at least one image of the scene illuminated from a second direction which is different from the first direction; and determining, based on the comparing, at least one shadow-related characteristic of the scene.