Robot Vacuum Distance Calibration Using Landmark Contact Feedback
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Solution Overview
Problem
Robotic vacuum cleaners face measurement errors due to changes in the angle and base line of structured light sources over time, caused by factors like temperature changes and vibrations, leading to inaccurate obstacle detection.
Innovation Solution
The robotic cleaning device autonomously calibrates parameters by identifying a landmark, estimating distance using structured light, and comparing it with actual distance measured through dead reckoning, allowing for detection and adjustment of measurement errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If the robotic cleaning device uses structured light and trigonometric algorithms to estimate distances, then obstacle detection capability is improved, but measurement precision deteriorates over time due to parameter changes from temperature and vibrations
Solution Approach 1:
The system performs preliminary calibration by identifying a landmark and calculating its position using structured light before moving to contact the landmark. This preliminary measurement establishes a baseline for detecting parameter drift, allowing the system to proactively identify and correct measurement errors before they significantly impact operation.
Solution Approach 2:
The system uses feedback by comparing the landmark position calculated from structured light measurements with the actual position determined through dead reckoning. This feedback loop enables the system to detect measurement errors and recalibrate parameters, maintaining measurement precision over time despite temperature and vibration changes.
2Ease of manufacture
If the device parameters are fixed during production, then manufacturing complexity is reduced, but adaptability deteriorates as parameters change over time due to environmental factors
Solution Approach 1:
The robotic cleaning device performs self-calibration by autonomously identifying landmarks, measuring distances using structured light, comparing with dead reckoning results, and adjusting its own parameters. This self-service capability allows the device to adapt to parameter changes from temperature and vibrations without requiring external recalibration or complex manufacturing processes.
Solution Approach 2:
The system dynamically adjusts calibration parameters based on detected measurement errors. By allowing parameters to change adaptively through the calibration process, the system maintains measurement accuracy despite environmental variations, resolving the contradiction between fixed manufacturing parameters and long-term parameter stability.
3Measurement precision
If external calibration is required to maintain accuracy, then measurement precision is improved, but device complexity and user burden increase
Solution Approach 1:
The calibration process is fully automated and performed by the device itself without external intervention. The system autonomously identifies landmarks, executes measurements, compares results, and adjusts parameters, eliminating the need for users to perform complex calibration procedures or seek external calibration services.
Solution Approach 2:
The landmark identification and calibration process leverages the existing structured light and dead reckoning systems already used for navigation and obstacle detection. By reusing these existing components for calibration purposes, the system achieves accurate self-calibration without adding separate dedicated calibration hardware or procedures.
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
This method enables continuous accurate measurement over a long period without the need for external calibration, enhancing the device's autonomy and user-friendliness by detecting and correcting measurement errors independently.
Implementation Method 1
estimating a distance to the landmark by illuminating the landmark with structured light and extracting information from the reflections of the structured light
Data Source
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AI summary
The invention relates to Robotic cleaning device (10, 10') comprising a main body (11), a propulsion system (12, 13, 15a, 15b), a contact detecting portion (32) connected to the main body (11), a dead reckoning sensor (30, 30') operatively connected to the propulsion system and an obstacle detecting device comprising a camera (23) and a first structured light source (27) arranged at a distance from each other on the main body. The robotic cleaning device may further comprise a processing unit (16) arranged to control the propulsion system. The obstacle detecting device and the processing unit are arranged to estimate a distance (DC) to the landmark and to subsequently move the robotic cleaning device into contact with the landmark while measuring an actual distance (DA) to the landmark, whereby the actual distance is then compared with the distance for detection of a measurement error.