Cleaning robot and method for performing task thereof
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Solution Overview
Problem
Conventional cleaning robots are limited in their ability to identify and respond to objects in their environment due to the limited combination of sensors, leading to ineffective task performance and object avoidance.
Innovation Solution
A cleaning robot equipped with multiple sensors and a camera, using a trained artificial intelligence model to generate a semantic map of the environment, allowing for precise object recognition and task execution based on user control commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a conventional cleaning robot uses limited sensors for object detection, then the device complexity is reduced, but the object recognition precision and task performance deteriorate
Solution Approach 1:
The patent segments the sensing system into multiple independent sensor modules, each responsible for detecting specific object attributes (e.g., one sensor for shape, another for texture, another for color). This segmentation allows the robot to achieve comprehensive object recognition precision while managing device complexity through modular design, where each sensor module can be independently optimized and replaced.
2Productivity
If the cleaning robot uses multiple sensors to identify objects, then the task performance improves, but the device complexity increases
Solution Approach 1:
The patent implements a universal sensor fusion module that can process data from multiple different sensor types (optical sensors, tactile sensors, depth sensors, etc.) through a unified processing framework. This multi-functional module enables the robot to perform various tasks (object identification, navigation, manipulation) using the same sensor combination, thereby improving task performance without proportionally increasing device complexity.
3Adaptability or versatility
If the cleaning robot avoids objects based solely on sensor detection capability, then the device complexity is minimized, but the adaptability to different object types deteriorates
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting sensor thresholds, detection sensitivity, and avoidance behavior parameters based on the identified object type. For example, when a fragile object is detected, the robot changes its movement parameters to be gentler; when a movable object is detected, it changes the avoidance parameter to attempt relocation. This allows high adaptability to different objects while keeping the control system complexity manageable through parameter adjustment rather than structural complexity.
Data Source
AI summary
A method for performing a task of a cleaning robot includes generating a navigation map for driving the cleaning robot using a result of at least one sensor detecting a task area in which an object is arranged, obtaining recognition information of the object by applying an image of the object captured by at least one camera to a trained artificial intelligence model, generating a semantic map indicating environment of the task area by mapping an area of the object included in the navigation map with the recognition information of the object, and performing a task of the cleaning robot based on a control command of a user using the semantic map.