Robot and method for controlling same
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Solution Overview
Problem
Existing robot cleaners face issues with positional accuracy and obstacle avoidance when map information is inaccurate, leading to potential loss of position and erroneous detection during autonomous travel.
Innovation Solution
A robot cleaner equipped with a sensing unit, such as a camera sensor, generates map information by determining driving cost values for each grid based on feature accuracy and environmental information, allowing it to set a travel path that avoids dangerous areas and ensures safe navigation to a destination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the robot cleaner travels autonomously using general map information, then it can navigate the cleaning area, but it may enter areas with insufficient information causing positional loss or erroneous detection
Solution Approach 1:
The system performs preliminary assessment of information quality for each grid cell before navigation. Map information is evaluated in advance to identify areas with insufficient features, and the path planning algorithm proactively avoids these areas, preventing positional loss before it occurs
Solution Approach 2:
A driving cost value is introduced as an intermediary parameter to evaluate and compare different path options. This cost value incorporates information quality metrics, allowing the system to select paths that balance navigation efficiency with position recognition reliability
2Measurement precision
If the robot cleaner collects sufficient environmental information for accurate position detection, then position recognition accuracy improves, but the system complexity and processing requirements increase
Solution Approach 1:
The cleaning area is divided into discrete grid cells, with each cell independently evaluated for information quality. This segmentation allows the system to process and assess local environmental features separately, reducing overall computational complexity while maintaining comprehensive coverage
Solution Approach 2:
The system transforms complex environmental information into a simplified driving cost value parameter. By converting diverse sensor data and feature information into a single comparable metric, the system reduces processing complexity while preserving the essential quality assessment needed for accurate navigation
3Loss of time
If the robot cleaner follows the shortest path to destination, then travel time is reduced, but it may pass through areas with inaccurate map information causing navigation errors
Solution Approach 1:
The path planning algorithm modifies the traditional shortest path criterion by incorporating driving cost values that reflect information quality. Paths are evaluated based on a composite metric that balances travel distance with navigation safety, selecting routes that minimize time loss while avoiding high-risk areas
Solution Approach 2:
The system uses driving cost values as feedback to continuously evaluate and adjust path selection. By incorporating information quality assessment into the path planning loop, the system can dynamically avoid areas with poor map information while maintaining efficient navigation performance
Data Source
AI summary
To successfully deal with a problem to be solved by the present invention, a cleaner for performing automatic driving according to an embodiment of the present invention comprises: a body; a driving unit for moving the body; a detecting unit for acquiring information relating to an environment around the body while the body runs in a cleaning area; and a control unit which generates map information corresponding to the cleaning area on the basis of the information acquired by the detecting unit, configures a driving cost value for each of multiple grids included in the map information, and configures a driving route of the body on the basis of the configured driving cost value.