Method for eliminating misjudgment of reflective light and optical sensing system
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Solution Overview
Problem
Autonomous robots often misjudge reflective light signals from highly reflective surfaces, leading to inaccurate obstacle detection and false alarms due to strong reflected signals overwhelming conventional algorithms.
Innovation Solution
A method that captures and analyzes frame images of reflective light signals, corrects erroneous information by referencing previous signal characteristics, and calculates confidence levels to exclude misjudged signals, ensuring accurate object detection by confirming the presence of objects only when signal strengths do not exceed a threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a light sensor is used to detect obstacles by sensing reflected detection lights, then the autonomous robot can navigate around the house, but misjudgments occur when receiving lights reflected by highly-reflective walls or floors
Solution Approach 1:
The patent segments the detection process into multiple independent analysis dimensions: center of gravity calculation, signal strength threshold comparison, and confidence level evaluation. By dividing the obstacle detection into these separate analytical components, the system can identify and eliminate erroneous detections from highly-reflective surfaces without compromising overall navigation functionality.
Solution Approach 2:
The patent introduces an intermediary verification mechanism that acts as a mediator between the light sensor input and the obstacle detection output. This intermediary layer analyzes signal characteristics, compares strengths against thresholds, and validates confidence levels before confirming obstacle presence, thereby preventing false alarms from highly-reflective surfaces while maintaining true obstacle detection.
2Device complexity
If conventional algorithms rely only on center of gravity of reflected lights for determination, then the processing is simple, but inaccurate distance calculation and false reports occur from highly reflected lights
Solution Approach 1:
The patent applies preliminary action by performing signal strength threshold comparison and confidence level evaluation before final obstacle confirmation. This preliminary analysis filters out erroneous signals from highly-reflective surfaces early in the processing chain, ensuring that only valid obstacle detections proceed to distance calculation and reporting, thereby improving measurement precision without significantly increasing complexity.
3Illumination intensity
If the light sensor receives strong reflected lights from highly-reflective objects, then the signal strength is high, but erroneous signals are generated causing false alarms
Solution Approach 1:
The patent converts the harmful effect of strong reflected lights from highly-reflective surfaces into a beneficial detection mechanism. By using signal strength threshold comparison and confidence level evaluation, the system transforms the previously harmful strong signals into identifiable patterns that trigger verification processes, thereby eliminating false alarms while maintaining the ability to detect true obstacles regardless of reflectivity.
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
Effectively eliminates misjudgment by improving the accuracy of obstacle detection and preventing false alarms in autonomous robots, even in highly reflective environments, by using corrected signal characteristics for precise distance calculation and object confirmation.
Implementation Method 1
a light sensor can be used to detect the obstacles by sensing detection lights emitted by a light source when the detection light is reflected by the obstacle on the navigation path
Data Source
AI summary
A method for eliminating misjudgment of a reflective light is provided. A light source emits a transverse linear light toward a direction of a floor as detection light and the light sensor senses reflective light signals from an object that reflects the detection light. In the method, a frame image including the reflective light signals is captured by the light sensor, centers of gravity of the reflective light signals are analyzed, and the centers of gravity of the reflective light signals can be corrected based on a line of gravity or a center of gravity of previous reflective light signals stored in a memory of the autonomous robot in order to exclude a center of gravity generated by the reflective light signal from a wall. A distance of the object can be confirmed based on the corrected centers of gravity of reflective light signals.