Time-of-Flight Sensor Active Power Control for Glare
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Solution Overview
Problem
Time-of-flight sensors are unreliable in environments with varied lighting and high reflectivity, leading to unsatisfactory pixel data, which can hinder obstacle detection and safety in autonomous vehicles.
Innovation Solution
Active power control of time-of-flight sensors by adjusting illumination power and integration time based on pixel data quality, using techniques such as varying illumination power and integration time to minimize saturation and underexposure, and employing pixel evaluation and power determination components to dynamically adjust sensor settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the time-of-flight sensor operates in high-illumination environments or near highly reflective objects, then the sensor can capture more light signals, but saturation occurs making it impossible to infer any information about the scene
Solution Approach 1:
The patent implements dynamic adjustment of the sensor's integration time based on real-time scene brightness analysis. The system continuously monitors the brightness of captured images and automatically adjusts the integration time parameter to optimize performance across varying illumination conditions, transforming a static sensor into an adaptive system that prevents saturation while maintaining signal capture capability
Solution Approach 2:
The system changes the integration time parameter dynamically based on scene conditions. When the scene is bright or contains highly reflective objects, the integration time is reduced to prevent saturation. When the scene is darker, the integration time is increased to capture sufficient light signals, thereby maintaining data reliability across different illumination environments
2Measurement precision
If the sensor increases processing time to better understand unreliable pixel data, then data accuracy may improve, but efficiency in identifying and characterizing objects decreases
Solution Approach 1:
The system performs preliminary analysis of scene brightness before object identification processing. By pre-adjusting the integration time based on brightness analysis, the sensor captures reliable data from the outset, eliminating the need for subsequent complex processing to correct unreliable pixel data, thus maintaining both accuracy and efficiency
Solution Approach 2:
The system implements a feedback loop where the brightness of captured images is continuously monitored and used to adjust the integration time for subsequent captures. This real-time feedback mechanism ensures that the sensor operates in an optimal range, producing reliable data that requires minimal post-processing while maintaining high object identification efficiency
3Ease of operation
If the sensor operates with fixed integration time and illumination power, then the system is simple to operate, but it cannot adapt to varied lighting conditions and different reflective properties of objects
Solution Approach 1:
The sensor system performs self-adjustment by automatically analyzing the brightness of captured scenes and autonomously modifying its integration time parameter. This self-service capability eliminates the need for manual configuration or complex external control systems, maintaining ease of operation while achieving high adaptability to varied lighting conditions and different object reflective properties
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
Improves sensor data reliability, enabling more accurate object detection and safer navigation by reducing the impact of environmental factors like glare and high reflectivity.
Implementation Method 1
Time-of-flight sensors may be unreliable in certain environments
Implementation Method 2
reflections off objects that are extremely close to the sensor, reflections off objects that have high reflectivity
Implementation Method 3
generating controls to adjust attributes of the sensor based on pixel data. The attributes can include illumination power and integration time
Implementation Method 4
high reflectivity may cause saturation, making it impossible to infer any information about the scene
Data Source
AI summary
Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Sensor data generated by the time-of-flight sensor can return unreliable pixels, e.g., in the case of over- or under-exposure. In some examples, parameters associated with power of a time-of-flight sensor can be altered based on a number of unreliable pixels in measured data and/or based on intensity values of the measured data. For example, unreliable pixels can be determined using phase frame information captured at a receiver of the sensor.