Vacuum cleaner
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Solution Overview
Problem
Conventional autonomous-traveling vacuum cleaners face challenges in accurately detecting obstacles due to limitations with ultrasonic and infrared sensors, leading to potential collisions or stagnation during cleaning.
Innovation Solution
The vacuum cleaner employs cameras positioned to overlap in their fields of view, allowing for depth calculation and obstacle discrimination based on images, enabling precise detection of obstacles and efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ultrasonic sensors are used for obstacle detection, then the vacuum cleaner can detect obstacles at a distance, but soft curtains, thin cords, and similar objects cannot be properly detected because they do not reflect ultrasonic waves effectively
Solution Approach 1:
The patent combines multiple detection methods (ultrasonic sensing, infrared sensing, and image pickup) into a unified obstacle detection system. The image pickup means captures visual information that complements the sensor data, enabling reliable detection of soft curtains, thin cords, and other objects that single sensors cannot detect effectively.
Solution Approach 2:
The image pickup means serves multiple functions: it detects obstacles, determines their material properties (soft/hard), assesses their shape characteristics, and provides visual confirmation for the control unit to make navigation decisions. This multi-functional approach replaces the need for multiple specialized sensors.
2Measurement precision
If infrared sensors are used for obstacle detection, then the vacuum cleaner can detect dark objects and thin cords, but black objects and thin cords cannot be properly detected because they absorb infrared rays rather than reflect them
Solution Approach 1:
The patent merges infrared sensing with image pickup technology. While infrared sensors detect thermal radiation, the image pickup means captures reflected visible light, providing complementary detection capabilities that overcome the limitations of infrared sensors in detecting black objects that absorb rather than reflect infrared rays.
Solution Approach 2:
The image pickup means acts as an intermediary detection mechanism that captures visual information about obstacles using visible light reflection, bypassing the limitation of infrared sensors when dealing with objects that absorb infrared radiation. This provides a fallback detection method for problematic objects.
3Reliability
If the vacuum cleaner improves obstacle detection precision using multiple sensors, then cleaning performance is improved with stable traveling, but the device complexity increases
Solution Approach 1:
The image pickup means performs multiple detection functions simultaneously: obstacle presence detection, material classification (soft/hard), shape assessment, and distance measurement. This consolidates what would otherwise require multiple specialized sensors into a single multi-functional component, reducing overall system complexity.
Solution Approach 2:
The image pickup means automatically provides comprehensive obstacle information without requiring additional processing sensors. The control unit extracts all necessary detection data (presence, material, shape) directly from the image data, eliminating the need for separate sensor systems for each detection function.
4Measurement precision
If the vacuum cleaner uses image pickup means to calculate depth and discriminate obstacles, then obstacle detection precision is improved, but the device complexity increases due to additional processing requirements
Solution Approach 1:
The image pickup means and control unit work together to automatically calculate depth information and discriminate obstacle types from the captured images. The control unit extracts depth, material, and shape information directly from the image data without requiring additional processing sensors or complex external systems, making the processing self-contained and efficient.
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 solution enhances obstacle detection precision, ensuring smoother and more effective cleaning by accurately identifying and avoiding obstacles, improving the overall cleaning performance and safety of the vacuum cleaner.
Implementation Method 1
The image pickup means are placed apart from each other in the main casing to pick up images on a traveling-direction side of the main casing with their fields of view overlapping with each other
Data Source
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AI summary
Provided is a vacuum cleaner (11) having improved obstacle detection precision. The vacuum cleaner (11) includes a main casing, driving wheels, a control unit (27), a cleaning unit (22), cameras (51), (52), and a depth calculation part (62). The driving wheels enable the main casing to travel. The control unit (27) controls drive of the driving wheels to make the main casing autonomously travel. The cleaning unit (22) cleans a floor surface. The cameras (51), (52) are disposed apart from each other in the main casing to pick up images on a traveling-direction side of the main casing with their fields of view overlapping with each other. The depth calculation part (62) calculates a depth of an object distanced from the cameras (51), (52) based on images picked up by the cameras (51), (52).