Cleaning Robot Dynamic Charging Control for Reduced Interruption Time
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Solution Overview
Problem
Current household cleaning robots inefficiently manage power consumption during charging, leading to prolonged cleaning interruptions and reduced overall cleaning efficiency.
Innovation Solution
A cleaning robot equipped with a navigation apparatus and control system that monitors cleaned areas in real time, calculates a to-be-cleaned area, and adjusts charging based on a total power consumption factor to ensure optimal power levels for continued cleaning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the cleaning robot charges to a fixed threshold (e.g., 80%) regardless of remaining cleaning tasks, then the power management is simple, but the cleaning efficiency is reduced due to unnecessary charging interruptions
Solution Approach 1:
The charging threshold is dynamically adjusted based on the remaining cleaning area. When the remaining area is small, the threshold is lowered to avoid unnecessary charging interruptions. When the remaining area is large, the threshold is raised to ensure sufficient power for continued cleaning. This dynamic adjustment optimizes cleaning efficiency while adapting to different operational contexts.
Solution Approach 2:
The system continuously monitors the cleaned area and calculates the remaining cleaning area in real-time. This feedback information is used to dynamically adjust the charging threshold, creating a closed-loop control system that optimizes power management based on actual cleaning progress and remaining tasks.
2Reliability
If the cleaning robot frequently returns to charge at fixed power thresholds, then the power level is maintained, but the overall cleaning time is extended due to repeated interruptions
Solution Approach 1:
The charging threshold dynamically adapts based on the proportion of remaining cleaning area. As the cleaning task progresses and less area remains, the threshold decreases, allowing the robot to complete final tasks without charging interruptions. This reduces total interruption time while maintaining sufficient power levels for each stage of cleaning.
Solution Approach 2:
The system changes the power threshold parameter based on the cleaning progress parameter. By linking the threshold to the remaining cleaning area proportion, the system optimizes the balance between maintaining reliable power levels and minimizing time loss from charging interruptions.
3Device complexity
If the cleaning robot uses a simple fixed-threshold charging strategy, then the control system is simple, but the power consumption management is inefficient
Solution Approach 1:
The control system incorporates real-time feedback from the navigation apparatus regarding the cleaned area. This feedback enables intelligent decision-making about when to charge, optimizing power consumption by charging only when necessary based on remaining tasks rather than following a fixed schedule.
Solution Approach 2:
The system autonomously calculates the remaining cleaning area and independently determines the optimal charging threshold without external intervention. This self-service capability improves power consumption efficiency while keeping the control logic relatively simple, as the robot uses its own operational data to make charging decisions.
Data Source
AI summary
Embodiments of the present disclosure provide a cleaning robot. The cleaning robot includes: a chassis; a drive system; an energy storage unit, configured to be charged according to a predetermined amount in a case that the robot is located at a charging station; a navigation apparatus, configured to monitor a cleaned area in real time; and a control system, wherein the navigation apparatus reports the cleaned area to the control system, and the control system is configured to calculate and obtain a to-be-cleaned area according to the cleaned area, and control the energy storage unit to be charged according to the predetermined amount based on a to-be-cleaned area and a total power consumption factor.