A method of controlling a mobile robot
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Solution Overview
Problem
Mobile robots, such as robotic vacuum cleaners, often require human intervention to resolve errors like airway blockages and slips, which can hinder their autonomous operation and user experience.
Innovation Solution
A method for controlling mobile robots that involves monitoring two systems to detect specific errors and determining a third error state when both are encountered, allowing the robot to perform targeted error-handling operations without user intervention, such as reducing suction power to navigate away from the error area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the robot reduces suction power to resolve limpet-state error, then the robot's mobility is improved, but the cleaning performance deteriorates
Solution Approach 1:
The robot dynamically adjusts the suction power based on the detected error state. When a limpet-state error is detected (combination of airway blockage and slip), the robot reduces suction power to improve mobility. When operating normally, the robot maintains high suction power for optimal cleaning performance. This dynamic adjustment resolves the contradiction by adapting the suction power to the current operational context.
2Measurement precision
If the robot performs comprehensive error monitoring and analysis, then the accuracy of error detection is improved, but the computational complexity increases
Solution Approach 1:
The error detection system is segmented into multiple independent monitoring components, each responsible for detecting specific error indicators in different systems (airway blockage in the cleaning system, slip in the drive system). The control system evaluates combinations of these segmented error detections to identify composite errors like limpet-state. This segmentation approach improves detection accuracy while keeping the control logic manageable through modular design.
3Extent of automation
If the robot autonomously resolves errors without human intervention, then the extent of automation is improved, but the reliability of error resolution may deteriorate
Solution Approach 1:
The robot employs feedback mechanisms to verify the effectiveness of error-resolution actions. After detecting an error and executing a resolution action (such as reducing suction power for limpet-state), the robot continues monitoring the error indicators to confirm whether the error state has been resolved. This feedback loop enhances the reliability of autonomous error resolution by ensuring that actions are effective before considering the problem solved.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances the robot's autonomy by enabling self-resolution of errors like limpet-state conditions, reducing the need for human interaction and improving cleaning performance across various floor types.
Implementation Method 1
a vacuum motor configured to generate a pressure difference to move air from the cleaner head through the cyclonic separator
Implementation Method 2
a cyclonic separator configured to separate dust from air flow
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
A method of controlling a mobile robot, the method comprising: monitoring a first system of the mobile robot to detect a first error associated with the first system; and monitoring a second system of the mobile robot to detect a second error associated with the second system, wherein when the first error and the second error are detected at the same time, determining that a third error has occurred.