Robot Pose Determination With Dual-Map LiDAR Frame Switching
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Solution Overview
Problem
Lidar odometer-based SLAM systems face precision issues due to frame matching errors that accumulate over time, leading to misalignment, and existing solutions either result in low mapping precision with fixed window sub-maps or require excessive calculations with sliding window sub-maps.
Innovation Solution
A method using two alternating maps with different frame counts to improve pose calculation precision, where lidar data frames are inserted into the map with a larger frame count only when sufficient, reducing unnecessary map reconstruction and calculation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed window sub-map is used for laser matching, then the device complexity is reduced, but the mapping precision deteriorates when the amount of lidar data frames is small
Solution Approach 1:
The patent implements dynamic map management by allowing the sub-map window size to vary based on the amount of lidar data frames available. When sufficient frames are accumulated, the window expands to improve mapping precision; when frames are limited, the window contracts to maintain operational simplicity. This dynamic adjustment resolves the contradiction between device complexity and mapping precision.
Solution Approach 2:
The patent changes the parameter of map window size from a fixed value to a variable that adapts based on data frame accumulation. By adjusting the window size parameter dynamically, the system achieves high mapping precision when data is sufficient while maintaining low complexity when data is limited, thus resolving the technical contradiction.
2Measurement precision
If a sliding window sub-map is used for laser matching, then the mapping precision is improved, but the computational overhead increases due to frequent map reconstruction
Solution Approach 1:
The patent implements periodic map reconstruction only when necessary, rather than continuously as in sliding window approaches. The system periodically checks whether the accumulated lidar data frames meet a threshold condition, and only triggers map reconstruction when the condition is satisfied. This periodic action maintains high mapping precision while significantly reducing computational overhead compared to continuous reconstruction.
Solution Approach 2:
The patent performs preliminary accumulation of lidar data frames before initiating map reconstruction. By preliminarily gathering sufficient data frames and only then reconstructing the map, the system ensures high mapping precision is achieved when reconstruction occurs, while avoiding unnecessary frequent reconstructions that would reduce calculation efficiency.
3Measurement precision
If lidar data frames are continuously accumulated in a sub-map, then the mapping precision is improved, but the loss of time increases due to delayed map updates
Solution Approach 1:
The patent implements a feedback mechanism that monitors the accumulation of lidar data frames and triggers map reconstruction when a threshold is reached. This feedback loop ensures that maps are updated at optimal intervals - not too frequently to avoid unnecessary computation, and not too infrequently to avoid excessive delays. The feedback mechanism balances mapping precision improvement with timely map updates.
Data Source
AI summary
The present disclosure provides a robot pose determination method including: collecting laser frames; calculating a current pose of the robot in a map pointed by a first pointer based on the laser frames, and obtaining an amount of the laser frames having been inserted into the map pointed by the first pointer; inserting the laser frames into a map pointed by the first pointer, if less than a first threshold; inserting the laser frames into the map pointed by the first pointer and a map pointed by a second pointer, if greater than or equal to the first threshold and less than a second threshold; and pointing the first pointer to the map pointed by the second pointer, pointing the second pointer to a newly created empty map, and inserting the laser frames into the map pointed by the first pointer, if equal to the second threshold.