Robotic Cleaning Device Speed Control for Multi-Surface Adaptability
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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
The implementation of a machine learning approach that uses real-time sensory input from environmental sensors to dynamically adjust the speed of components like the main brush and wheels based on predicted environmental characteristics, creating a debris map and adjusting operational parameters to suit specific cleaning needs.
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 speed adjustment by enabling the robotic device to autonomously modify the speed of its main brush and peripheral brushes in real-time based on environmental conditions. The processor continuously receives sensor data about surface type and adjusts rotational speeds accordingly, transforming a static system into an adaptive one that optimizes cleaning performance across hardwood, carpet, and tile surfaces without requiring manual intervention or complex mechanical adjustment mechanisms.
Solution Approach 2:
The system changes operational parameters (brush speeds) based on detected environmental conditions. The processor analyzes sensor data to identify surface types and automatically adjusts the rotational speed parameters of the main brush and peripheral brushes to optimal values for each surface type, enabling versatile cleaning performance through software-controlled parameter modification rather than hardware complexity.
2Productivity
If the robotic cleaning device increases brush speed for better cleaning, then cleaning effectiveness improves, but the risk of stalling or entanglement increases
Solution Approach 1:
The system implements feedback control by continuously monitoring sensor data about environmental conditions and adjusting brush speeds in response. The processor receives real-time information about surface type, debris presence, and operational status, then modifies brush speeds to maintain optimal cleaning effectiveness while avoiding conditions that would cause stalling or entanglement. This closed-loop control ensures high productivity without sacrificing reliability.
Solution Approach 2:
The brush speeds are dynamically adjusted based on real-time environmental assessment rather than maintaining fixed high speeds. The system transitions between different speed regimes according to surface conditions, enabling high cleaning effectiveness on suitable surfaces while automatically reducing speeds on surfaces prone to causing stalling or entanglement, thus maintaining both productivity and reliability.
3Productivity
If the robotic cleaning device operates at high speed continuously, then cleaning productivity is high, but noise disturbances increase
Solution Approach 1:
The system dynamically adjusts operational speeds based on environmental context and cleaning needs rather than maintaining continuous high-speed operation. The processor evaluates surface type, debris distribution, and cleaning progress to optimize speed settings, achieving high productivity when conditions permit while reducing speeds to minimize noise in appropriate situations, thus balancing productivity with noise reduction.
Data Source
AI summary
A robot including a main brush; a peripheral brush; a first actuator; a first sensor; processors; and memory storing instructions that when executed by the processors effectuate operations. The operations include determining a first location of the robot in a working environment; obtaining first data from the first sensor or another sensor indicative of a value of an environmental characteristic of the first location; adjusting a first operational parameter of the first actuator based on the sensed first data; 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.