Reflectance Map Construction via Global Pose Optimization
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Solution Overview
Problem
Current methods for constructing reflectance maps in navigation systems, which rely on GPS and inertial navigation devices, suffer from errors due to satellite signal shifts and error accumulation, leading to reduced precision in positioning vehicles.
Innovation Solution
A method and apparatus that select key frame laser point clouds, perform global pose optimization on non-optimal key frames, and construct reflectance maps using the optimized positions and Euler angles of laser radar centers, improving the accuracy of coordinates in the world coordinate system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS and inertial navigation devices are used to provide position and Euler angle data for laser point cloud construction, then the reflectance map can be constructed using available navigation data, but the positioning precision deteriorates due to satellite signal shifts and error accumulation
Solution Approach 1:
The patent implements a feedback mechanism by comparing the position and Euler angle data from GPS/inertial navigation devices with the actual laser point cloud data. The system calculates adjustment amounts based on the differences between expected and actual laser point cloud positions, and uses this feedback to optimize the navigation data, thereby improving positioning precision while maintaining the use of available navigation devices.
Solution Approach 2:
The patent changes the parameters of the position and Euler angle data by applying optimization adjustments. The system modifies the navigation data parameters based on the adjustment amounts calculated from laser point cloud comparisons, transforming the original imprecise navigation data into optimized parameters that achieve higher positioning precision.
2Area of stationary object
If all laser point clouds are used for reflectance map construction without selection, then the map coverage is complete, but the processing complexity and computational time increase significantly
Solution Approach 1:
The patent segments the laser point clouds into different categories: key frame laser point clouds (selected based on specific criteria) and non-key frame laser point clouds. This segmentation allows the system to process only the essential key frame data for optimization while still using all data for comprehensive map construction, thereby reducing processing complexity while maintaining complete map coverage.
Solution Approach 2:
The patent applies partial action by selecting only key frame laser point clouds for the optimization process rather than processing all laser point clouds. This partial processing approach reduces computational complexity while the final reflectance map construction still utilizes comprehensive data to ensure complete area coverage.
3Measurement precision
If key frame laser point clouds are selected and optimized to improve positioning accuracy, then the reflectance map precision improves, but the algorithm complexity and computational requirements increase
Solution Approach 1:
The patent segments the laser point cloud data into key frame and non-key frame subsets, applying optimization only to the key frame data. This segmentation strategy reduces algorithm complexity by limiting the optimization scope to essential frames while still achieving improved reflectance map precision through the optimized key frame positions and Euler angles.
Data Source
AI summary
A specific implementation of the method includes: constructing a reflectance map based on a position and an Euler angle, obtained through a global pose optimization and used for constructing a reflectance map, of a center of a laser radar corresponding to each frame laser point cloud used for constructing the reflectance map. This implementation implements the level-by-level pose optimization of key frame laser point clouds, sample frame laser point clouds, regular frame laser point clouds selected from laser point clouds used for constructing a reflectance map, to obtain an accurate position and Euler angle, used for constructing the reflectance map, of a center of the laser radar corresponding to each frame laser point cloud used for constructing the reflectance map, so that accurate coordinates of laser points in each frame laser point cloud used for constructing the reflectance map in a world coordinate system can be obtained.