Stereo Camera Correction Using LiDAR Distance Feedback
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Solution Overview
Problem
Existing sensor systems face challenges in accurately estimating distances to objects, particularly when objects are outside the ideal range, non-reflective, or have surfaces not normal to the sensor's pointing direction, leading to unreliable distance measurements due to interference or limited field-of-view.
Innovation Solution
A system combining a rotating active sensor, such as LIDAR, with a stereo camera system, where the controller compares distance estimates from both systems to calculate correction factors, allowing for accurate distance estimation by modifying stereo camera data with error factors derived from active sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR sensor is used to estimate distance, then distance measurement is improved for reflective surfaces, but measurement reliability deteriorates for non-reflective objects or objects with surfaces not normal to the pointing direction
Solution Approach 1:
The patent combines LIDAR distance measurements with stereo camera measurements into a unified distance estimation system. The LIDAR provides accurate measurements for reflective surfaces while the stereo camera provides complementary measurements for non-reflective objects, and their results are merged through a combination algorithm to achieve reliable distance estimation across all object types.
2Area of stationary object
If stereo camera system is used to estimate distance, then field-of-view coverage is improved, but measurement accuracy deteriorates for objects outside ideal range
Solution Approach 1:
The system uses LIDAR measurements as feedback to correct and refine stereo camera distance estimates. The LIDAR provides accurate reference measurements that are used to calculate correction factors, which are then applied to the stereo camera measurements to improve their accuracy for objects at various ranges.
3Device complexity
If single sensor system is used, then device complexity is reduced, but measurement reliability deteriorates in challenging conditions
Solution Approach 1:
The patent changes the operational parameters of the sensor system by using LIDAR at higher frequencies than the stereo camera. This parameter change allows the system to capture temporal variations in the scene and improve measurement reliability by comparing measurements taken at different time points, particularly for moving objects or changing lighting conditions.
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 combination improves distance estimation accuracy by leveraging the strengths of both active and passive sensors, providing reliable measurements even in challenging conditions by comparing and adjusting data from LIDAR and stereo cameras.
Implementation Method 1
The transmitter emits light pulses toward an environment of the LIDAR sensor. The receiver detects reflections of the emitted light pulses.
Implementation Method 2
Individual points in the point cloud can be determined, for example, by transmitting a laser pulse and detecting a returning pulse, if any, reflected from an object in the environment, and then determining a distance to the object according to a time delay between the transmission of the pulse and the reception of its reflection.
Implementation Method 3
Each CMOS sensor may receive a portion of light from the scene incident on the array. Each CMOS sensor may then output a measure of the amount of light incident on the CMOS sensor during an exposure time
Data Source
AI summary
One example system comprises an active sensor that includes a transmitter and a receiver, a first camera that detects external light originating from one or more external light sources to generate first image data, a second camera that detects external light originating from one or more external light sources to generate second image data, and a controller. The controller is configured to perform operations comprising determining a first distance estimate to a first object based on a comparison of the first image data and the second image data, determining a second distance estimate to the first object based on active sensor data, comparing the first distance estimate and the second distance estimate, and determining a third distance estimate to a second object based on the first image data, the second image data, and the comparison of the first and second distance estimates.