Spin Mop Robot Position Correction for Slip-Aware Distance Tracking
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Solution Overview
Problem
Mobile robots without wheels, which rely on frictional force for movement, face challenges in accurately detecting position and correcting for slipping, especially when using image sensors, leading to inefficient cleaning patterns and incomplete coverage around corners and walls.
Innovation Solution
A mobile robot design incorporating a sensing module that detects moving distance and speed without relying on wheel rotation, using a combination of encoders, obstacle sensors, and image sensors to correct for slipping and maintain accurate position tracking, allowing for patterned cleaning regardless of water level changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a lower image sensor is used to detect position, then position detection capability is improved, but power consumption increases and data processing becomes difficult
Solution Approach 1:
The patent divides the sensing system into multiple components: upper image sensor for absolute position, lower image sensor for relative position correction, and encoder for rotation detection. Each sensor handles a specific aspect of position detection, allowing the system to achieve high accuracy without overloading a single sensor with excessive processing requirements
Solution Approach 2:
The lower image sensor acts as an intermediary that corrects position errors detected by the upper image sensor. Instead of relying solely on the power-intensive lower sensor, the system uses the lower sensor to provide correction data that refines the overall position accuracy while reducing the processing burden on the lower sensor
2Device complexity
If the robot moves only by frictional force of the spin mop, then wheel structure is simplified, but position correction becomes difficult without wheel rotation data
Solution Approach 1:
The patent replaces the traditional wheel-based mechanical system with a spin mop-based frictional propulsion system. Position correction is achieved not through wheel rotation counting but through image sensor data processing and encoder detection of spin mop rotation, substituting mechanical measurement with optical and electromagnetic sensing
Solution Approach 2:
The system implements feedback control by continuously comparing the expected position (calculated from spin mop rotation) with the actual position (detected by image sensors). The encoder provides rotation feedback, and image sensors provide position feedback, allowing the system to correct for slipping and maintain accurate position tracking despite the lack of traditional wheel rotation data
3Device complexity
If random traveling is used for cleaning, then navigation complexity is reduced, but cleaning thoroughness decreases especially near corners and walls
Solution Approach 1:
The image sensors provide continuous feedback about the robot's position and the cleaning coverage achieved. This feedback enables the system to transition from purely random traveling to a more intelligent navigation pattern that can identify and target areas requiring cleaning, including corners and walls that would be missed by random motion alone
Solution Approach 2:
The navigation system dynamically adjusts its behavior based on real-time sensor data. Rather than sticking to a fixed random traveling pattern, the robot can modify its path in response to detected surfaces, obstacles, and cleaning status, enabling it to adaptively cover difficult-to-reach areas while maintaining the overall simplicity of the navigation approach
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
The solution enables accurate position detection and correction for slipping, ensuring thorough and efficient cleaning patterns even around corners and walls, improving cleaning effectiveness and reliability.
Implementation Method 1
a mobile robot, which is not driven by wheels but moves by a frictional force between a spin mop and a floor
Implementation Method 2
a sensing module which is disposed at a lower surface of the body, and obtains at least any one data of a moving distance or a moving speed during a predetermined period of time by detecting a lower part of the body
Data Source
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AI summary
The present disclosure relates to a mobile robot and a method of calculating a moving distance of the mobile robot, the mobile robot including: a spin mop which includes a rotary plate, which is rotatable transversely, and slips while moving; an encoder which obtains any one or more data from the rotary plate, and transmits the obtained data to a controller; a sensing module which obtains at least any one data of a moving distance or a moving speed during a predetermined period of time by detecting external circumstances; and a controller configured to process the data, in which by calculating a moving distance or a rotation angle based on the data obtained by the encoder, and by correcting the moving distance or the rotation angle based on the data obtained by the sensing module, a final moving distance or rotation angle may be calculated accurately.