Dual-AI Object Detection for Obstructed Hazard Avoidance
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Solution Overview
Problem
Conventional electronic apparatuses fail to identify objects 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 AI models – one for object identification and another for identifying partially obstructed dangerous objects – determines distances and controls movement to avoid collisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single AI model is used to identify objects, then the device complexity is reduced, but the ability to identify partially blocked objects deteriorates
Solution Approach 1:
The patent divides the object identification task into two separate AI models: a first AI model for identifying completely visible objects and a second AI model for identifying partially blocked objects. This segmentation allows each model to be specialized for its specific task, improving overall identification accuracy while maintaining manageable complexity through modular architecture.
2Productivity
If the electronic apparatus travels close to identified objects, then productivity is improved, but the risk of collision with blocked objects increases
Solution Approach 1:
The patent performs preliminary identification of partially blocked objects using the second AI model before the electronic apparatus travels close to any objects. By detecting blocked objects in advance and determining their distances, the system can pre-plan a safe trajectory that avoids collisions while still allowing efficient cleaning of visible areas.
3Device complexity
If conventional object identification methods are used, then the device complexity is low, but the measurement precision of blocked objects deteriorates
Solution Approach 1:
The patent introduces an intermediary processing step where the second AI model acts as a mediator to detect partially blocked objects that the first model misses. The system processes the same image through both models, and the second model's specialized detection capability complements the first model's general object recognition, achieving high measurement precision without significantly increasing overall system complexity.
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.