Self-Propelled Device IMU Positioning Adjustment
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Solution Overview
Problem
Self-propelled devices, such as smart mowers, face challenges in maintaining accurate positioning due to varying lawn surface conditions, which can lead to inaccurate inertial data and potential toppling over when encountering slopes.
Innovation Solution
The integration of a traveling wheel assembly, an IMU, and a controller that statistically analyzes inertial data within a specific time window to adjust positioning parameters, improving positioning accuracy and slope angle identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inertial data is collected by IMU for positioning, then positioning function is provided, but positioning accuracy deteriorates due to lawn surface undulations affecting inertial data
Solution Approach 1:
The system performs statistical analysis on inertial data within a time window to detect surface condition changes, then uses this feedback to adjust the fusion weight of inertial data dynamically. When surface undulations are detected (high variance in inertial data), the system reduces the weight of inertial data in positioning fusion, thereby maintaining positioning accuracy despite harsh surface conditions.
Solution Approach 2:
The system dynamically changes the positioning parameter (fusion weight of inertial data) based on statistical analysis of inertial data variance. By adjusting this parameter according to detected surface conditions, the system optimizes positioning accuracy adaptively - using higher inertial data weight on flat surfaces and lower weight on undulating surfaces.
2Adaptability or versatility
If smart mower operates on diverse terrains, then adaptability is improved, but slope angle identification accuracy deteriorates leading to toppling risk
Solution Approach 1:
The system uses statistical analysis of inertial data as feedback to assess surface conditions and adjust positioning parameter fusion weights. This feedback mechanism enables the system to adapt to diverse terrains while maintaining accurate slope angle identification by reducing reliance on inertial data when surface undulations are detected.
Solution Approach 2:
The system dynamically adjusts the fusion weight of inertial data based on real-time statistical analysis of surface conditions. This dynamic adaptation allows the mower to maintain stable operation on diverse terrains - using inertial data effectively on flat surfaces while reducing its influence on undulating surfaces to prevent toppling.
3Extent of automation
If inertial data fusion is used for positioning, then positioning functionality is achieved, but positioning accuracy deteriorates on bumpy surfaces
Solution Approach 1:
The system automatically changes the fusion weight parameter of inertial data based on statistical analysis of surface conditions. This parameter adjustment maintains automated positioning functionality while adapting to surface conditions - preserving high automation level while improving accuracy on bumpy surfaces by reducing inertial data influence when variance is high.
Data Source
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AI summary
Provided is a self-propelled device. The self-propelled device includes a body; a traveling wheel assembly configured to support the body; an inertial measurement unit (IMU) disposed in the body and including at least one of an accelerometer and a gyroscope; and a controller electrically connected to the IMU and configured to control the self-propelled device to travel; receive inertial data from the IMU; and statistically analyze the inertial data received within a first time window and adjust a positioning parameter of the IMU according to a statistical result. The positioning parameter of the inertial data is adjusted according to the statistical result of the inertial data of the self-propelled device, and the positioning of the self-propelled device calculated using the adjusted positioning parameter is more accurate.