Ground-Intensity LiDAR Registration for Degenerate Road Geometry
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Solution Overview
Problem
Conventional LIDAR localization systems struggle to provide accurate pose estimates in geometrically degenerate areas such as long stretches of highways, bridges, and tunnels, where insufficient geometric constraints lead to multiple valid solutions and reduced localization accuracy.
Innovation Solution
The introduction of a ground intensity LIDAR localizer that utilizes the intensity signal from LIDAR returns on the ground to complement geometric information, enabling pose estimates based on material reflectivity and improving localization accuracy in degenerate areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional geometric LIDAR localization is used, then the system works well in environments with sufficient geometric features, but localization accuracy deteriorates in geometrically degenerate areas such as highways, bridges, and tunnels
Solution Approach 1:
The patent combines geometric LIDAR data with intensity LIDAR data to create a hybrid localization system. The geometric localizer processes 3D point cloud geometry while the intensity localizer processes reflectivity values, and their results are fused to achieve accurate localization in both geometrically rich and degenerate environments, resolving the contradiction between precision in specific environments and adaptability across all environments.
Solution Approach 2:
The patent adds the intensity dimension to the traditional geometric LIDAR data. Instead of relying solely on 3D spatial coordinates (x, y, z), the system incorporates intensity values (reflectivity) as an additional dimension of information. This allows the localization system to distinguish features based on material properties rather than just geometry, enabling operation in previously challenging environments.
2Reliability
If only geometric information is used for localization, then the system is simpler to implement, but it cannot provide reliable pose estimates in areas with insufficient geometric constraints
Solution Approach 1:
The patent makes the LIDAR system multi-functional by extracting both geometric information and intensity information from the same sensor. The single LIDAR sensor serves dual purposes: providing 3D spatial data for geometric localization and providing reflectivity data for intensity-based localization. This eliminates the need for additional specialized sensors while improving reliability across diverse environments.
Solution Approach 2:
The patent introduces an intensity-based localizer as an intermediary system that bridges the gap in geometrically degenerate areas. When geometric features are insufficient, the intensity localizer provides alternative constraints through reflectivity patterns. The two localizers work complementarily, with the intensity localizer acting as a mediator to maintain reliability when the geometric localizer fails.
3Measurement precision
If LIDAR intensity data is incorporated into localization, then localization accuracy improves in geometrically degenerate areas, but the processing complexity increases
Solution Approach 1:
The patent segments the localization task into two independent but complementary components: geometric processing and intensity processing. Each component has its own dedicated localizer that processes its respective data type using optimized algorithms. This segmentation allows each processor to be specialized and efficient, reducing the overall computational burden compared to a monolithic approach that tries to process all data together.
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
The ground intensity LIDAR localizer enhances localization accuracy and robustness by fusing geometric and intensity-based pose estimates, effectively extending the operational range of localization systems into previously challenging environments.
Implementation Method 1
ground intensity LIDAR localizer that utilizes the intensity signal from LIDAR returns on the ground
Implementation Method 2
intensity signal from LIDAR returns on the ground to complement geometric information, enabling pose estimates based on material reflectivity
Data Source
AI summary
A system for determining a pose of a vehicle and building maps from vehicle priors processes received ground intensity LIDAR data including intensity data for points believed to be on the ground and height information to form ground intensity LIDAR (GIL) images including pixels in 2D coordinates where each pixel contains an intensity value, a height value, and x- and y-gradients of intensity and height. The GIL images are formed by filtering aggregated ground intensity LIDAR data falling into a same spatial bin on the ground and using a registration algorithm to align two GIL images relative to one another by estimating a 6-degree-of-freedom pose with associated uncertainty that minimizes error between the two GIL images. The aligned GIL images are provided as a pose estimate to a localizer. The system may provide online localization and pose estimation, prior building, and prior to prior alignment pose estimation using image-based techniques.