SLAM Map Refinement With Contextual Trajectory Constraints
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Solution Overview
Problem
High accuracy mapping using GPS or GNSS is hindered by signal outages and obstructions, and SLAM outputs lack context for validation and analysis without additional sensor data and constraint information.
Innovation Solution
A computing system that generates maps using a SLAM algorithm, providing additional context by obtaining and depicting sensor data, determining positions and orientations, and displaying graphical illustrations of trajectory points and constraints, allowing for the selection and modification of constraints to refine the mapping process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SLAM algorithm is used to generate maps without GPS, then mapping accuracy is maintained in signal-denied environments, but the ability to validate and analyze the outputs becomes difficult
Solution Approach 1:
The patent introduces an intermediary visualization system that mediates between the SLAM algorithm outputs and the user. This system displays trajectory points, sensor data, and constraint information in an integrated graphical interface, allowing users to validate and analyze SLAM results without needing direct access to raw computational data. The intermediary translates complex algorithmic outputs into interpretable visual representations.
Solution Approach 2:
The patent segments the SLAM validation process into distinct visualizable components: trajectory points, sensor data frames, constraints, and their relationships. By breaking down the complex SLAM output into separable visual elements, users can individually examine and validate each component, thereby recovering the lost context information needed for thorough analysis.
2Loss of information
If additional sensor data and constraint information are provided for SLAM validation, then the ability to analyze and validate outputs is improved, but the system complexity increases
Solution Approach 1:
The patent creates a universal visualization interface that handles multiple types of data (trajectory points, sensor frames, constraints) and multiple validation tasks through a single integrated system. This multi-functional interface reduces the need for separate tools and procedures for different aspects of SLAM validation, thereby managing system complexity while providing comprehensive analysis capabilities.
Solution Approach 2:
The patent creates visual copies and representations of the underlying sensor data and constraint structures without requiring users to manipulate the actual complex data structures. The graphical interface copies essential information in simplified forms, allowing validation without direct engagement with the complex raw data, thus maintaining analytical capability while reducing system complexity.
3Measurement precision
If GPS is used for high accuracy mapping, then mapping precision is improved, but the system fails in signal outage and obstruction conditions
Solution Approach 1:
The patent implements feedback mechanisms where the visualization system displays constraint satisfaction status and trajectory validation results back to the user. This feedback loop allows users to assess the quality of SLAM outputs and make informed decisions about map reliability, effectively compensating for the lack of GPS by providing measurable indicators of mapping accuracy through alternative means.
Data Source
AI summary
A computing system includes one or more processors and a memory storing instructions that, when executed by the one or more processors, cause the system to perform operations. The operations include obtaining sensor data from a sensor of a vehicle, the sensor data including point cloud frames at different positions, orientations, and times, the sensor data used to generate a map, determining a position and an orientation of the sensor corresponding to a capture of each of the point cloud frames according to a simultaneous localization and mapping (SLAM) algorithm, and depicting, on an interface, a graphical illustration of the determined positions at which the point cloud frames were captured.