Mobile robot and control method thereof
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Solution Overview
Problem
Current robot cleaners rely on multiple sensors or complex systems to detect obstacles during autonomous travel, which increases costs and complexity, while there is a need for a solution that can effectively use a single camera for obstacle detection and control.
Innovation Solution
A robot cleaner equipped with a main body, suction opening, driving unit, camera sensor, and controller that captures images, segments them, and uses various methods such as image comparison and feature point extraction to detect obstacles, allowing for obstacle avoidance using a monocular camera.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensors or complex systems are used for obstacle detection, then detection reliability is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The single camera sensor performs multiple functions: obstacle detection, distance estimation, and navigation guidance. By making the camera multi-functional, the system achieves reliable obstacle detection without requiring multiple specialized sensors, thus reducing device complexity while maintaining detection reliability
Solution Approach 2:
The system changes the operational parameters of the single camera through image processing techniques (segmentation, feature extraction, comparison algorithms) to achieve reliable obstacle detection. By transforming the camera's output data through multiple processing stages, the system compensates for the limitations of using a single sensor
2Measurement precision
If multiple sensors are used for obstacle detection, then measurement precision is improved, but manufacturing cost increases
Solution Approach 1:
The system creates multiple virtual copies of the camera's image data through processing (segmented image regions, feature points, projected images) to achieve precise obstacle detection. Instead of using multiple physical sensors, the system generates multiple processed versions of the single camera's output, reducing manufacturing cost while maintaining measurement precision
Solution Approach 2:
The patent replaces a mechanical/multiple-sensor system with an optical system (single camera) combined with computational processing. By substituting physical multiple sensors with a single sensor plus image processing algorithms, the system achieves precise obstacle detection at lower manufacturing cost
3Device complexity
If a single camera is used for obstacle detection, then device complexity is reduced, but detection precision deteriorates
Solution Approach 1:
The camera image is segmented into multiple regions (foreground, background, obstacle regions) through image processing. This segmentation allows the single camera to precisely identify and distinguish obstacles from the environment, compensating for the inherent limitations of monocular vision and improving detection precision while maintaining low device complexity
Solution Approach 2:
The system compensates for the lack of depth information in a single camera by introducing temporal dimension (comparing images captured at different times) and processing dimension (multiple image processing stages including segmentation, feature extraction, and projection). This multi-dimensional approach enables precise obstacle detection using only a single camera
Data Source
AI summary
A cleaner performing autonomous traveling includes a main body having a suction opening, a cleaning unit provided within the main body and sucking a cleaning target through the suction opening, a driving unit moving the main body, a camera sensor attached to the main body and capturing a first image, an operation sensor sensing information related to movement of the main body, and a controller detecting information related to an obstacle on the basis of at least one of the captured image and the information related to movement and controlling the driving unit on the basis of the detected information related to the obstacle.