Surfel-Map SLAM for Reliable Pose Estimation in Sparse Scenes
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Solution Overview
Problem
Existing SLAM algorithms struggle with datasets containing limited identifiable features, high speeds, and dynamic objects, leading to unreliable pose estimation and map generation.
Innovation Solution
A SLAM algorithm that models the optimization problem as a factor graph, incrementally creating and solving it using surfel maps based on 3D ellipsoids, incorporating environmental sensor data and optional additional resources like inertial and GPS data, to handle diverse and demanding datasets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing SLAM algorithms are used with datasets containing limited identifiable features, high speeds, and dynamic objects, then the algorithms can process the data, but the pose estimation and map generation become unreliable
Solution Approach 1:
The patent changes the fundamental parameters of map representation from traditional point clouds or feature-based maps to surfel maps (surface elements). This parameter change enables reliable pose estimation in environments with limited features by representing surfaces as oriented surface elements with normal vectors and covariance matrices, which provide more robust geometric constraints for pose estimation even when few distinguishable features are present.
Solution Approach 2:
The patent segments the environment into discrete surfel units that can be independently processed and accumulated. Each surfel represents a local surface patch with specific geometric properties, allowing the system to build up reliable pose estimates through incremental accumulation of constraints from multiple surfels, rather than relying on a few prominent features.
2Productivity
If SLAM algorithms are optimized for computing speed to work directly in mobile systems, then navigation support is improved, but flexibility to handle different sensor configurations and demanding datasets is reduced
Solution Approach 1:
The patent creates a universal SLAM framework based on factor graphs that can accommodate multiple sensor types (LiDAR, cameras, inertial sensors, GPS) and different data configurations through a unified mathematical model. The factor graph structure allows optional inclusion of different sensor factors, making the system adaptable to various resource configurations while maintaining computational efficiency through incremental optimization.
Solution Approach 2:
The patent implements dynamic adaptability by allowing the factor graph to be incrementally built and reconfigured as new sensors or data sources become available. The system can dynamically add or remove factor types (ego-motion factors, surfel factors, sensor-specific factors) based on the actual sensor configuration, providing flexibility without sacrificing computing speed through pre-computed optimizations.
3Productivity
If the mobile system moves at high speed, then productivity is improved, but the similarity of sensor data between consecutive frames makes feature mapping difficult and reduces pose estimation accuracy
Solution Approach 1:
The patent performs preliminary surfel map construction and maintains an up-to-date surfel representation of the environment before pose estimation is needed. By pre-processing sensor data into surfel features and maintaining their spatial relationships in the factor graph, the system has ready-to-use geometric constraints available even when the vehicle moves quickly between frames, eliminating the need for complex real-time feature matching at high speeds.
Data Source
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AI summary
The invention relates to a computer-implemented method for determining an ego-pose of a mobile system and creating a Surfel map of an environment based on 3D ellipsoids using an optimization problem represented by a factor graph (10), in which new Surfels (16) and previously known Surfels are identified by comparing Surfel data with a Surfel map, and a Surfel factor (14a, 14a') is added to a factor graph (10) for the Surfels (16) identified as previously known, and/or a Surfel node (12b) and a Surfel factor (14a) are added to the factor graph (10) for Surfels (16) identified as newly identified. The invention further relates to a data processing device comprising means for carrying out the above method, and to a computer program product comprising instructions that, when the program is executed by a computer, cause it to carry out the above method.Furthermore, the invention relates to a computer-readable data carrier on which the above computer program product is stored.