Robot Cleaner Path Adjustment for Dynamic Obstacle Movement
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Solution Overview
Problem
Existing robot cleaners inefficiently clean complex areas and do not account for obstacle movement, leading to ineffective cleaning paths when obstacles change positions.
Innovation Solution
A robot cleaner system that generates a cleaning map with obstacle locations and types, allows user input for setting cleaning paths, and adjusts paths based on obstacle movement, using image and obstacle sensors to detect and classify obstacles, and a network interface for user communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If robot cleaners avoid obstacles in cleaning area, then cleaning safety is improved, but cleaning efficiency in complicated areas deteriorates
Solution Approach 1:
The cleaning path is dynamically adjusted based on obstacle movement detection. The system transitions from static obstacle avoidance to dynamic path planning that adapts to changing obstacle positions, enabling the robot to efficiently clean complicated areas while maintaining safety by continuously monitoring obstacle locations.
2Device complexity
If robot cleaners use preset cleaning paths, then cleaning path determination is simplified, but adaptability to moving obstacles deteriorates
Solution Approach 1:
The system uses feedback from sensors to detect obstacle positions and movements, then adjusts the cleaning path accordingly. This feedback mechanism allows the robot to maintain simple path determination logic while adapting to moving obstacles by continuously receiving updated position information and modifying the path based on this feedback.
3Loss of information
If robot cleaners provide detailed cleaning maps to users, then user understanding of cleaning area is improved, but user interface complexity deteriorates
Solution Approach 1:
The system creates a simplified visual copy or representation of the cleaning map that displays obstacle locations and cleaning paths in an intuitive format. This visual copy allows users to understand the cleaning area and obstacle positions without exposing them to the underlying system complexity, maintaining ease of operation while providing comprehensive information.
Data Source
AI summary
Provided are a robot cleaner using an artificial intelligence (AI) and/or machine learning algorithm in a 5G environment connected for the Internet of Things and a method for determining a cleaning path of a robot cleaner. The method for determining a cleaning path includes detecting an obstacle, identifying a type of the obstacle based on the image signal, generating a cleaning map including information on the identified obstacle, providing the cleaning map to a user terminal, receiving an input of a cleaning pattern for an area of the obstacle from the user terminal, and determining a cleaning path including the cleaning pattern for the area of the obstacle.