LiDAR Drift Correction via Map Point Cloud Integration

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Solution Overview

Problem

Existing technologies for estimating the position and posture of a mobile body in an absolute coordinate system face challenges, including the inability of LiDAR-based systems to estimate absolute positions without accurate calibration between LiDAR and IMU, and the need for precise calibration to achieve high estimation accuracy.

Innovation Solution

A method and device for accurately estimating the position and posture of a mobile body in an absolute coordinate system by acquiring three-dimensional point cloud data and position data, estimating local and absolute positions and postures, and generating corrected absolute positions and postures through integration with map point cloud data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If LiDAR-based position estimation is used, then relative position can be estimated, but absolute position estimation accuracy deteriorates due to LiDAR drift

Engineering Contradiction:

Improveposition estimation accuracyVSAvoidabsolute position reliability

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent introduces map point cloud data as an intermediary reference frame to correct LiDAR drift. The correction unit uses map point cloud data to adjust and correct position estimation results, thereby eliminating the harmful effect of LiDAR drift while maintaining the benefits of LiDAR-based relative positioning.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent implements a feedback mechanism where position estimation results are continuously corrected using map point cloud data. The correction unit receives position estimates and feedback from map data to iteratively improve accuracy, resolving the contradiction between relative positioning capability and absolute position reliability.

Inventive Principle:

Principle #23Feedback

2Measurement precision

If LiDAR and IMU calibration is performed, then absolute position estimation accuracy improves, but device complexity increases

Engineering Contradiction:

Improveposition estimation accuracyVSAvoidcalibration complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent extracts the calibration requirement from the core positioning system by using map point cloud data as an external reference. Instead of requiring complex calibration between LiDAR and IMU, the system uses pre-existing map data to provide absolute position references, thereby reducing device complexity while maintaining accuracy.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent replaces complex, long-term calibration procedures with simpler, periodic corrections using map point cloud data. The correction unit applies straightforward transformations based on map data without requiring sophisticated calibration hardware or procedures, reducing overall system complexity.

Inventive Principle:

Principle #27Cheap short-living objects (Disposable)

3Measurement precision

If frequent position data acquisition is performed, then estimation accuracy improves, but energy consumption increases

Engineering Contradiction:

Improveposition estimation accuracyVSAvoidenergy consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent performs preliminary actions by using map point cloud data to correct position estimates at longer intervals. The correction unit applies corrections based on pre-existing map data, which reduces the frequency of active sensing and processing, thereby lowering energy consumption while maintaining accuracy through periodic refinements.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent implements periodic correction using map point cloud data rather than continuous high-frequency processing. The correction unit operates at intervals, applying corrections based on periodic position data acquisition, which reduces energy consumption compared to continuous estimation while maintaining sufficient accuracy for the application.

Inventive Principle:

Principle #19Periodic action

Data Source

PatentUS20250037402A1Position posture estimation method, position posture estimation device, and program

Publication Date: 2025.01.30 NIPPON TELEGRAPH & TELEPHONE CORP

AI summary

A position and posture estimation device acquires three-dimensional point cloud data at each of times and position data at each of times, the three-dimensional point cloud data being measured every time a first time elapses, the position data being measured every time a second time longer than the first time elapses. The position and posture estimation device estimates a local position in a local coordinate system and a local posture in the local coordinate system. The position and posture estimation device estimates an estimated absolute position and an estimated absolute posture in an absolute coordinate system every time the position data is acquired. The position and posture estimation device generates provisional three-dimensional point cloud data in the absolute coordinate system every time the position data is acquired. The position and posture estimation device generates composite data obtained by integrating the provisional three-dimensional point cloud data and map point cloud data generated from three-dimensional point cloud data previously measured, and corrects the estimated absolute position and the estimated absolute posture to increase a degree of coincidence between the composite data and the map point cloud data.