Robot Infrared Obstacle Detection Using Ambient Light Compensation
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Solution Overview
Problem
Existing infrared obstacle detection devices for robots are prone to erroneous detection due to the influence of ambient light, particularly sunlight, which contains broadband light waves that can activate the reception module and lead to false obstacle detection.
Innovation Solution
The implementation of a dual-reception module system where one module receives reflected infrared light and the other receives ambient infrared light, allowing for a comparison of energy levels to determine if the detected infrared light is from an obstacle or ambient sources, with detection confirmed when the energy difference exceeds a preset threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single reception module is used to detect infrared light, then the device structure is simple, but the detection accuracy is reduced due to ambient light interference
Solution Approach 1:
The reception function is segmented into two separate modules: a first reception module for receiving reflected infrared light from obstacles, and a second reception module for receiving ambient infrared light. This segmentation allows independent measurement of each light source, enabling subsequent subtraction to eliminate ambient light interference and improve detection accuracy.
Solution Approach 2:
The second reception module acts as an intermediary that measures the ambient infrared light background. By introducing this intermediate measurement, the system can compensate for environmental interference and isolate the signal from reflected infrared light, thereby improving detection precision.
2Ease of operation
If the reception module receives all infrared light without discrimination, then the detection process is simple, but false detection occurs due to ambient infrared light
Solution Approach 1:
The detection process is segmented into two parallel measurement channels: one for reflected infrared light and one for ambient infrared light. This segmentation maintains operational simplicity while improving reliability by enabling the system to distinguish between valid obstacle signals and false ambient light signals through comparative analysis.
Solution Approach 2:
The system uses feedback from the second reception module (measuring ambient light) to compensate for environmental interference in the first reception module. By continuously monitoring ambient infrared light levels and subtracting them from the total received signal, the system eliminates false detections while maintaining a simple detection process.
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 approach effectively reduces the impact of ambient light on obstacle detection accuracy, enhancing the reliability of infrared obstacle detection by distinguishing between reflected and ambient infrared light, thereby improving detection precision.
Implementation Method 1
controlling an emission module to radiate infrared light to the outside
Implementation Method 2
acquiring first infrared light received by a first reception module and second infrared light received by a second reception module
Data Source
AI summary
The present invention discloses an infrared obstacle detection method and device and a robot. The method comprises the following steps: controlling an emission module to radiate infrared light to the outside; acquiring first infrared light received by a first reception module and second infrared light received by a second reception module, wherein the first reception module is disposed relative to the emission module such that the first infrared light comprises reflected light obtained by reflecting, by an obstacle, the infrared light radiated by the emission module to the outside and infrared light in ambient light, and the second reception module is disposed relative to the emission module such that the second infrared light is the infrared light in the ambient light; and comparing the first infrared light and the second infrared light, and determining that the obstacle is detected when an energy difference between the first infrared light and the second infrared light is larger than a preset threshold.