Artificial intelligence robot for managing movement of object using artificial intelligence and method of operating the same
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Solution Overview
Problem
Conventional robot cleaners are limited in their ability to recognize and manage small objects, often failing to pick them up or avoiding them altogether, which restricts their cleaning functionality.
Innovation Solution
An artificial intelligence robot equipped with an object recognition model and a delivery location inference model, capable of identifying objects and moving them to a determined location using a driving motor, ensuring that small objects are not overlooked or misplaced.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the robot cleaner uses conventional object recognition methods, then it can recognize relatively large objects, but it fails to recognize and properly handle relatively small objects
Solution Approach 1:
The patent segments the cleaning area into multiple zones and categorizes objects by size into different groups (small objects like rings, medium objects, large objects). This segmentation allows the robot to apply different handling strategies to different object categories, improving both recognition accuracy and handling versatility across various object sizes.
Solution Approach 2:
The patent changes the parameter of object size classification by introducing specific size thresholds and categories. By defining small objects (e.g., rings) separately from larger objects, the system adjusts its behavior parameters accordingly - avoiding small objects that shouldn't be suctioned while still navigating around larger obstacles, thereby improving adaptability to different object sizes.
2Reliability
If the robot cleaner avoids all recognized objects, then it prevents suction of large objects, but it may also neglect to pick up small objects that should be collected
Solution Approach 1:
The patent introduces dynamic behavior adjustment based on object characteristics. Instead of a static avoid-all-objects rule, the robot dynamically changes its response: avoiding small objects like rings that shouldn't be suctioned, while actively navigating to pick up medium-sized objects that should be collected. This dynamic adaptation improves cleaning reliability without complicating the overall operation.
Solution Approach 2:
The system uses feedback from object recognition and classification to adjust its cleaning behavior. By continuously identifying object types and sizes, the robot receives feedback that informs whether to avoid, pick up, or navigate around each object, thereby improving cleaning reliability through adaptive decision-making while maintaining ease of operation through automated responses.
3Adaptability or versatility
If the robot cleaner only performs cleaning function, then the system remains simple, but it cannot provide object management and delivery services
Solution Approach 1:
The patent applies multi-functionality by enabling the robot to perform both cleaning and object management tasks using the same hardware platform. The robot can identify, categorize, avoid, pick up, and deliver objects in addition to its cleaning function. This universality increases functional capability while managing system complexity by reusing existing sensors, processors, and actuators for multiple purposes.
Solution Approach 2:
The robot performs preliminary object recognition and classification during its cleaning operations before executing specific actions. By identifying and categorizing objects in advance, the system prepares for subsequent actions (avoidance, pickup, or delivery) without requiring additional complex decision-making processes, thereby enhancing versatility while controlling system complexity through pre-planned response protocols.
Data Source
AI summary
An artificial intelligence robot for managing movement of an object using artificial intelligence includes a driving motor, a camera configured to acquire image data, a memory configured to store an object recognition model used to recognize the object from the image data and store a delivery location inference model for inferring a delivery location of the recognized object and a processor configured to recognize the object from the image data using the object recognition model, determine the delivery location of the recognized object from identification data of the recognized object using the delivery location inference model, and control the driving motor to move the artificial intelligence robot to the determined delivery location.