Robotic vacuum cleaner and control method therefor
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Solution Overview
Problem
Robot cleaners face inefficiencies in creating reliable cleaning maps due to incorrect obstacle registration, leading to reduced cleaning efficiency and accuracy, as they may not accurately determine whether detected obstacles can be avoided during map creation.
Innovation Solution
The robot cleaner employs an angle measurement sensor to assess the angle and distance of obstacles relative to its movement direction, categorizing areas as danger zones, travelable areas, or areas that can be overcome by rotation, thereby improving obstacle recognition and map reliability without additional detection sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robot cleaner uses basic obstacle detection and escaping algorithms, then the device complexity is low, but the cleaning map reliability deteriorates due to incorrect obstacle registration and jungle occurrence
Solution Approach 1:
The patent introduces angle measurement as a new dimension for obstacle assessment. By measuring the angle between the robot's movement direction and the obstacle, the system can determine whether an obstacle is avoidable without adding complex detection sensors. This angular dimension transforms the obstacle evaluation from a simple detection-based binary decision to a geometric assessment that improves map reliability.
Solution Approach 2:
The patent changes the parameter used for obstacle evaluation from basic detection presence to angle measurement. By using the angle parameter (θ) between the robot's movement direction and the obstacle, the system can categorize obstacles into avoidable and non-avoidable types, thereby improving cleaning map reliability without significantly increasing device complexity.
2Productivity
If the robot cleaner registers all detected obstacles on the cleaning map, then the obstacle detection coverage is complete, but the cleaning efficiency deteriorates due to jungle occurrence and incorrect area determination
Solution Approach 1:
The patent applies local quality by differentiating obstacle registration based on the specific characteristics of each obstacle. Instead of uniformly registering all obstacles, the system evaluates each obstacle's angle and determines its avoidability. Only non-avoidable obstacles are registered on the cleaning map, while avoidable obstacles are ignored, thereby preventing jungle occurrence and improving cleaning efficiency.
Solution Approach 2:
The patent inverts the traditional approach by not registering all detected obstacles but rather registering only those that cannot be avoided. This inversion prevents the jungle problem where cleanable areas are incorrectly marked as non-cleanable, thereby improving both obstacle information accuracy and cleaning efficiency.
3Measurement precision
If the robot cleaner uses multiple detection sensors to improve obstacle recognition accuracy, then the measurement precision improves, but the device complexity and cost increase
Solution Approach 1:
The patent makes the angle measurement sensor serve multiple functions: it measures both the position of obstacles and the robot's movement direction, and uses this information to determine obstacle avoidability. This multi-functionality improves obstacle recognition accuracy without requiring additional specialized sensors, thereby avoiding increased device complexity.
Data Source
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AI summary
A robot vacuum cleaner of the present invention comprises: a main body including a driving unit for moving the cleaner; an obstacle detection sensor disposed in the main body so as to detect an obstacle; a tilt measurement sensor for obtaining tilt information of the main body; a storage unit for storing a cleaning map produced on the basis of danger zones including the zone where an obstacle is located; and a control unit for allowing the cleaner to perform cleaning while the main body moves and avoids the danger zones contained in the cleaning map, wherein the control unit determines whether the main body can pass through an obstacle on the basis of the tilt information of the main body, and when the obstacle is determined as an obstacle which restricts the travel of the main body, records the zone in which the obstacle is located as the danger zone on the cleaning map.