Robotic Vacuum Speed Control for Surface-Adaptive Cleaning
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Solution Overview
Problem
Robotic cleaning devices often fail to optimize their cleaning performance across different environmental surfaces, such as hardwood and carpet, due to inadequate adjustment of suction or wheel speed settings, leading to suboptimal cleaning results.
Innovation Solution
An autonomous robotic cleaning device equipped with sensors and processors that dynamically adjust the speed of its components, such as the main brush and wheels, based on real-time environmental data, creating a debris map to identify areas with high debris accumulation and adjusting settings accordingly to optimize cleaning efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the robotic cleaning device uses fixed suction or wheel speed settings, then the device structure is simple and easy to control, but the cleaning performance is suboptimal across different environmental surfaces
Solution Approach 1:
The patent implements dynamic adjustment of wheel speed and suction power based on real-time sensor feedback about surface type (carpet, hardwood, tile). The controller continuously modifies operational parameters rather than using fixed settings, enabling the device to adapt to different surfaces while maintaining a relatively simple overall structure through automated control
Solution Approach 2:
The device incorporates sensors that detect environmental characteristics and provide feedback to the controller, which then adjusts suction and wheel speed accordingly. This closed-loop feedback system enables adaptive cleaning performance without requiring complex manual intervention or overly complicated mechanical structures
2Productivity
If the robotic cleaning device increases suction power and wheel speed for all surfaces, then cleaning effectiveness on carpet improves, but energy consumption increases and noise disturbance worsens
Solution Approach 1:
The device applies different suction power and wheel speed settings localized to specific surface types detected by sensors. High power is applied only when carpet is detected, while hardwood and tile surfaces receive lower power settings, optimizing energy consumption by matching performance to local environmental conditions rather than using uniform high power everywhere
Solution Approach 2:
The controller dynamically changes operational parameters (suction power, wheel speed) based on detected surface characteristics. This parameter adjustment enables the device to maintain high cleaning effectiveness on challenging surfaces like carpet while reducing energy consumption and noise on harder surfaces where less power is needed
3Productivity
If the robotic cleaning device moves quickly across all surfaces, then cleaning speed and productivity improve, but cleaning effectiveness on carpet deteriorates and entanglement with obstacles increases
Solution Approach 1:
The device dynamically adjusts wheel speed based on surface type and debris detection. When carpet or high-debris areas are detected, the device automatically reduces speed to ensure effective cleaning and prevent entanglement, while maintaining higher speeds on clear hard surfaces to preserve overall productivity
Solution Approach 2:
Sensors detect environmental characteristics including surface type and debris presence, providing feedback that triggers speed adjustments. This feedback mechanism enables the device to slow down automatically when conditions require more careful cleaning, reducing entanglement risks while maintaining efficient progress through less challenging areas
Data Source
AI summary
Provided is a robot including main and peripheral brushes; a first actuator; a first sensor; one or more processors; and memory storing instructions that when executed by the one or more processors effectuate operations including: determining a first location of the robot in a working environment; obtaining, with the first sensor or another sensor, first data indicative of an environmental characteristic of the first location; adjusting a first operational parameter of the first actuator based on the sensed first data to cause the first operational parameter to be in a first adjusted state while the robot is at the first location; and forming or updating a debris map of the working environment based on data output by the first sensor or the another sensor configured to collect data indicative of an existence of debris on a floor of the working environment over at least one cleaning session.