Robot Cleaner Path Planning by Floor Type and Battery Priority
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Solution Overview
Problem
Existing robot cleaners determine movement paths solely based on obstacle information without considering space characteristics or battery remaining capacity, leading to inefficient cleaning and frequent returns to charging stations.
Innovation Solution
A robot cleaner that identifies cleaning modes based on floor materials and remaining battery power, sets movement paths by prioritizing subspaces, and adjusts cleaning modes and paths dynamically using sensors and memory-stored information about space layouts and material properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot cleaner determines movement path only based on obstacle information, then the navigation is simple, but the cleaning efficiency is low
Solution Approach 1:
The space is divided into multiple subspaces, each with different cleaning modes assigned based on floor material characteristics. This segmentation allows the robot to optimize cleaning efficiency for different areas while maintaining manageable navigation complexity through systematic categorization.
Solution Approach 2:
The robot performs preliminary mapping of the space and identifies floor material characteristics before actual cleaning. This preliminary action enables pre-planning of movement paths and cleaning modes, improving cleaning efficiency without requiring complex real-time decision-making during operation.
2Productivity
If the robot cleaner does not consider battery remaining amount, then the control is simple, but the robot frequently returns to charging station
Solution Approach 1:
The robot calculates and plans the movement path in advance based on the remaining battery amount and power consumption requirements of different subspaces. This preliminary power management planning ensures continuous cleaning operation by preventing battery depletion, while maintaining relatively simple control logic through pre-computed paths.
Solution Approach 2:
The movement path is dynamically adjusted based on the remaining battery amount. When battery level changes, the robot recalculates the optimal path considering power consumption characteristics of different cleaning modes, enabling adaptive continuous operation without excessive control complexity.
3Productivity
If the robot cleaner uses uniform cleaning mode for all areas, then the control is simple, but the cleaning quality varies
Solution Approach 1:
Different cleaning modes are assigned to different subspaces based on their floor material characteristics. This local quality approach enables optimized cleaning quality for each area (e.g., stronger suction for carpets, standard mode for hard floors) while managing complexity through systematic classification of cleaning zones.
Data Source
AI summary
A robot cleaner is provided. A robot cleaner includes a cleaner main body, a battery configured to supply a power, a memory configured to store floor material information corresponding to each of a plurality of subspaces configuring a space, and a processor configured to identify a cleaning mode corresponding to each of the plurality of subspaces based on the floor material information corresponding to each of the plurality of subspaces, identify an order of priority of each of the plurality of subspaces based on the identified cleaning mode and a remaining amount of power, and set a movement path of the robot cleaner based on the identified order of priority.