Robot Virtual Wall Detection Using Dynamic Signal Threshold Adjustment
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Solution Overview
Problem
Cleaning robots face challenges in navigating complex environments due to the lack of clear boundaries, leading to potential damage or incorrect navigation when virtual walls are not accurately identified, as existing systems either allow the robot to enter restricted areas or require user intervention.
Innovation Solution
A robot system that uses a detection component to identify virtual walls by adjusting signal thresholds, allowing the robot to travel along the outer side of the virtual wall, preventing entry into restricted areas while avoiding misjudgment of other objects as virtual walls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed signal threshold is used to identify virtual walls, then the robot can operate with simple control logic, but the robot may misidentify objects or fail to accurately recognize virtual walls in complex environments
Solution Approach 1:
The patent implements dynamic threshold adjustment by switching between a first signal threshold during approach phase and a second signal threshold during alignment phase. The controller dynamically changes the threshold value based on the robot's position relative to the virtual wall, allowing accurate identification while maintaining simple control logic.
Solution Approach 2:
The patent changes the signal threshold parameter from a fixed value to a dynamically adjustable value. By modifying the threshold parameter based on detection signals and positional information, the system achieves both simple control logic and high identification accuracy in complex environments.
2Device complexity
If the robot uses a single signal threshold for virtual wall detection, then the system structure remains simple, but the robot cannot reliably distinguish virtual walls from other objects in complex environments
Solution Approach 1:
The detection system uses dynamic threshold switching based on the robot's approach distance and signal strength. The controller adjusts which threshold is active based on real-time conditions, enabling reliable virtual wall detection without complicating the overall system structure.
Solution Approach 2:
The detection process is segmented into different phases (approach phase and alignment phase), each using an appropriate threshold. This segmentation allows the simple detection system to achieve high reliability by applying the right threshold at the right time.
3Reliability
If the robot enters restricted areas due to inaccurate virtual wall identification, then the navigation system fails to protect the robot, but increasing detection sensitivity may cause the robot to avoid legitimate cleaning areas
Solution Approach 1:
The patent changes the threshold parameter dynamically to balance protection and productivity. During approach, a higher threshold ensures restricted areas are protected, while during alignment, the threshold adjustment allows the robot to confidently navigate along the virtual wall without avoiding legitimate cleaning areas.
Solution Approach 2:
Different threshold values are applied at different spatial locations and detection phases. The first threshold applies during approach to protected areas, while the second threshold applies during alignment along the virtual wall, ensuring both protection and productivity are maintained in their respective zones.
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 system effectively prevents the robot's driving wheel from entering restricted areas, ensuring safe operation and automated cleaning in complex environments without user intervention by accurately identifying virtual walls using adjusted signal thresholds.
Implementation Method 1
detect a virtual wall signal via a detection component
Implementation Method 2
the detection component includes at least one of a magnetometer, a Hall sensor, or an infrared sensor
Data Source
AI summary
A robot includes a controller configured to: detect a virtual wall signal; identify a virtual wall according to a signal threshold and the virtual wall signal; and when the virtual wall is identified, adjust the signal threshold, and control the robot to travel along an outer side of the virtual wall according to an adjusted signal threshold and the virtual wall signal, such that a driving wheel of the robot is located at the outer side of the virtual wall when the robot is traveling along the outer side of the virtual wall; wherein the outer side of the virtual wall is a side of the virtual wall within an active region of the robot.