Camera-LIDAR Alignment for Autonomous Vehicle Navigation
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately navigating roadways due to the difficulty in correlating LIDAR system outputs with visual information from cameras, which affects the determination of navigational characteristics such as road elevation and vehicle speed.
Innovation Solution
A system that includes cameras and LIDAR, where a processor aligns LIDAR reflection information with images captured by the camera to attribute navigational characteristics, such as road elevation and vehicle speed, by determining relative alignment matrices for rotation and translation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR and camera data are correlated to improve navigation accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines LIDAR reflection data and camera image data into a unified navigation system. The processor correlates LIDAR range information with visual object identification to create integrated navigational characteristics, merging two separate sensing modalities into a single coherent navigation decision-making system that improves accuracy while managing complexity through systematic data fusion.
2Reliability
If multiple sensors (camera and LIDAR) are integrated to enhance navigation capability, then reliability is improved, but device complexity increases
Solution Approach 1:
The system uses feedback by continuously comparing LIDAR reflection measurements with camera-identified object positions and characteristics. The processor adjusts navigational decisions based on correlated data from both sensors, creating a feedback loop that enhances reliability through cross-validation of sensor data while managing complexity through systematic integration.
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 alignment enables accurate determination of navigational characteristics, enhancing the vehicle's ability to safely navigate by correlating depth information from LIDAR with visual data from cameras, improving navigation precision.
Implementation Method 1
receive an output of a LIDAR onboard the host vehicle, wherein the output of the LIDAR is representative of a plurality of laser reflections from at least a portion of the environment surrounding the host vehicle
Implementation Method 2
receive a stream of images captured by a camera onboard the host vehicle, wherein the captured images are representative of an environment surrounding the host vehicle
Data Source
AI summary
Systems and methods are provided for navigating an autonomous vehicle. In one implementation, a navigational system for a host vehicle may include at least one processor programmed to: receive a stream of images captured by a camera onboard the host vehicle, wherein the captured images are representative of an environment surrounding the host vehicle; and receive an output of a LIDAR onboard the host vehicle, wherein the output of the LIDAR is representative of a plurality of laser reflections from at least a portion of the environment surrounding the host vehicle. The at least one processor may also be configured to determine at least one indicator of relative alignment between the output of the LIDAR and at least one image captured by the camera; attribute LIDAR reflection information to one or more objects identified in the at least one image based on the at least one indicator of the relative alignment between the output of the LIDAR and the at least one image captured by the camera; and use the attributed LIDAR reflection information and the one or more objects identified in the at least one image to determine at least one navigational characteristic associated with the host vehicle.