Dual-AI Object Detection for Occluded Obstacle Navigation
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Solution Overview
Problem
Conventional electronic apparatuses fail to identify objects that are partially blocked by other objects, leading to potential collisions and damage during navigation.
Innovation Solution
An electronic apparatus equipped with a camera, sensor, and dual artificial intelligence models to identify objects and dangerous objects, even when partially obscured, and control its movement to avoid collisions by determining distances between objects and dangerous objects using sensing data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional object identification methods are used, then the system is simple and fast, but it cannot identify objects that are partially blocked by other objects
Solution Approach 1:
The patent divides the object identification task into two separate AI models: one for identifying visible objects and another for inferring blocked objects. This segmentation allows each model to specialize in specific detection tasks, improving overall accuracy while managing system complexity through modular architecture
Solution Approach 2:
The patent introduces an intermediary inference mechanism that uses the relationship between visible objects and potentially blocked objects. The second AI model acts as a mediator that predicts the presence of blocked objects based on the detection results and spatial relationships, enabling indirect detection of obscured objects
2Reliability
If the electronic apparatus avoids all detected objects, then collision prevention is improved, but navigation efficiency decreases due to excessive caution
Solution Approach 1:
The patent applies different avoidance strategies based on the type of object detected. Critical objects that pose collision risks trigger avoidance maneuvers, while non-critical objects allow continued navigation. This localized application of avoidance behavior maintains safety for important objects while preserving navigation efficiency overall
Solution Approach 2:
The system dynamically adjusts navigation parameters based on object classification. When blocked objects are detected, the apparatus modifies its path planning parameters to account for the inferred object positions, changing navigation behavior only when and where necessary rather than applying uniform caution throughout the environment
Data Source
AI summary
Provided is an electronic apparatus, including: a sensor; a camera; a storage configured to store first and second artificial intelligence models; a first processor; and a second processor. The second processor is configured to: input an image obtained through the camera to the first artificial intelligence model and identify the object of the first type in the image, and input the image obtained through the camera to the second artificial intelligence model and identify the object of the second type, at least a part of which is not viewable in the image. The first processor is configured to: determine a distance between the object of the first type and the object of the second type based on sensing data received from the sensor; and control the electronic apparatus to travel based on the determined distance.