ToF Robot Localization Using Map Features in Reduced Light
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Solution Overview
Problem
Existing localization methods for mobile robots, such as those used in delivery robots, face challenges in achieving precise localization during low-light conditions, particularly when line-based localization techniques become inaccurate due to reduced visibility.
Innovation Solution
The use of time-of-flight (ToF) sensors to capture and process images, extracting features like straight lines and light sources, which allows for accurate localization even in low-light environments by generating a location hypothesis based on comparisons with map data, combining with visual cameras for enhanced accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If line-based localization techniques are used during daytime, then localization accuracy is improved, but localization accuracy deteriorates during low-light conditions
Solution Approach 1:
The patent changes the sensing parameter from visible light detection to infrared detection. The ToF sensor operates in the infrared spectrum, which allows it to detect features and measure distances independently of visible light conditions. This parameter change enables the system to maintain localization accuracy during low-light conditions by using a different portion of the electromagnetic spectrum that is not affected by illumination intensity.
Solution Approach 2:
The patent replaces the visual camera-based line detection system with a ToF sensor-based distance measurement system. Instead of using mechanical/optical line detection that relies on visible light, the system uses electromagnetic time-of-flight measurement to extract geometric features and determine localization. This substitution eliminates the dependency on visible light illumination.
2Measurement precision
If visual cameras are used for feature extraction, then localization accuracy is improved in good light conditions, but feature detection becomes unreliable in low-light conditions
Solution Approach 1:
The patent changes the detection parameter from visible light intensity to infrared time-of-flight measurement. The ToF sensor measures the time for infrared light to travel to and from objects, providing depth and distance information that is independent of ambient visible light conditions. This parameter change ensures reliable feature detection and extraction regardless of illumination levels.
3Measurement precision
If ToF sensors are used to capture images in low-light conditions, then localization accuracy is improved, but device complexity increases
Solution Approach 1:
The patent makes the ToF sensor perform multiple functions: it captures depth information, extracts geometric features (such as lines and planes), and provides localization data. By integrating these functions into a single sensor system, the patent reduces overall system complexity compared to using separate sensors for each function. The ToF sensor replaces the need for separate depth sensors and visual cameras, achieving multi-functionality.
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 enables highly accurate localization and navigation of mobile robots in low-light conditions by leveraging ToF sensors' ability to detect features under reduced light, improving localization accuracy and integrating with visual data for robust navigation.
Implementation Method 1
at least one time-of-flight (ToF) sensor (10) configured to capture at least one ToF sensor image
Data Source
AI summary
A method for localization using at least one time-of-flight (ToF) sensor, map data and a processing unit. The method can comprise capturing at least one ToF sensor image comprising at least one feature with the at least one ToF sensor. The method can further comprise the processing unit extracting at least one feature from the at least one ToF sensor image and the processing unit comparing the at least one extracted feature with the map data. A location hypothesis based on the comparison step can be generated and output. The present invention also relates to a localization system comprising a ToF sensor configured to capture a at least one ToF sensor image, a memory unit, comprising stored therein map data and a processing unit. The processing unit can be configured to extract at least one feature from the at least one ToF sensor image. The processing unit can further be configured to access the memory unit comprising the map data and compare the at least one extracted feature with the map data. The processing unit can generate a location hypothesis based on the comparison of the at least one extracted feature with the map data.