Optical Obstacle Sensing With Dual-Scan Reflection Verification
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Solution Overview
Problem
Autonomous robots face misjudgments due to strong reflective signals from highly-reflective surfaces, leading to false alarms and navigation errors, as conventional light sensors struggle to differentiate between reflective lights and actual obstacles.
Innovation Solution
An optical sensing system employing multiple light sources and a processor to capture and analyze reflection patterns from horizontal and vertical linear lights, allowing for the differentiation between actual objects and misjudgments caused by reflective surfaces, thereby adjusting navigation accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a conventional light sensor is used to detect obstacles, then the robot can navigate around the house, but misjudgments occur when receiving lights reflected by highly-reflective walls or floors
Solution Approach 1:
The detection area is divided into multiple segments including a first detection area for horizontal scanning and a second detection area for vertical scanning. The processor separately processes reflection patterns from each segment, enabling differentiated analysis of reflective signals from different spatial zones to reduce misjudgments
Solution Approach 2:
The system transitions from single-direction (horizontal) light scanning to multi-directional scanning by adding vertical light scanning. This dimensional expansion allows the system to capture reflection patterns from both horizontal and vertical perspectives, enabling better discrimination between true obstacles and reflective surfaces
2Quantity of substance
If the light sensor receives strong reflective signals, then the sensor can detect the presence of surfaces, but false alarms are generated due to signal strength exceeding detection thresholds
Solution Approach 1:
The processor analyzes reflection patterns by comparing signal characteristics against established criteria and adjusts detection thresholds dynamically. The system uses feedback from the reflection pattern analysis to distinguish between strong signals from reflective surfaces and strong signals from actual obstacles, reducing false alarms
Solution Approach 2:
The system changes the parameters of light emission by using both horizontal and vertical scanning directions with different light sources. This parameter variation creates distinct reflection pattern signatures that help differentiate between reflective surfaces and obstacles, even when signal intensities are similar
3Measurement precision
If multiple light sources are added to scan different areas, then the system can differentiate between obstacles and reflective surfaces, but the device complexity increases
Solution Approach 1:
The processor serves multiple functions by performing both horizontal and vertical reflection pattern analysis using the same processing unit. The light sensor module is designed to handle both horizontal and vertical scanning operations, reducing the need for completely separate detection systems and minimizing overall device complexity
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 eliminates misjudgments by comparing reflection patterns, ensuring accurate obstacle detection and preventing false alarms, thereby improving the navigation accuracy of autonomous robots in environments with highly reflective surfaces.
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
An optical sensing system is provided. The optical sensing system includes a first light source, a second light source, a light sensor, and a processor. The processor is configured to: control the first light source to scan a horizontal detection area; control the light sensor to capture a first frame by receiving first reflective lights from the horizontal detection area; obtain a first reflection pattern, and analyze the first reflection pattern to determine whether an object is within the first portion; if so, control the second light source to scan a first vertical detection area; control the light sensor to capture a second frame from the first vertical detection area; process the second frame to obtain a second reflection pattern, and analyze the second reflection pattern to determine whether the object is detected by a misjudgment.