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Enhancing Off-Road Topography Estimation by Fusing LIDAR and Stereo Camera Data with Interpolated Ground Plane
Gustav Sten1, Lei Feng1, Björn Möller1
1Engineering Design, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.
This study introduces an improved topography estimation method for autonomous navigation by interpolating Light Detection and Ranging (LIDAR) data. This approach significantly enhances stereo camera accuracy across various terrains.
Area of Science:
- Robotics
- Computer Vision
- Geospatial Analysis
Background:
- Accurate topography estimation is crucial for autonomous off-road navigation.
- Current methods using stereo cameras offer dense data but lack accuracy, while Light Detection and Ranging (LIDAR) sensors provide accuracy but limited coverage.
- Existing sensor fusion techniques often fail to leverage the full potential of LIDAR data due to direct integration limitations.
Purpose of the Study:
- To investigate if incorporating interpolated LIDAR data can significantly improve stereo camera-based topography estimation accuracy.
- To develop a novel sensor fusion method that expands the accuracy benefits of LIDAR beyond its direct scan areas.
- To evaluate the proposed method's effectiveness in diverse environments.
Main Methods:
- Constructing a reference ground plane by interpolating LIDAR data to match stereo camera point cloud coverage.
- Fusing interpolated LIDAR maps with stereo camera point clouds using Kalman filters for enhanced topography mapping.
- Testing the method in controlled indoor, semi-controlled outdoor, and unstructured terrain environments.
Main Results:
- The proposed method demonstrated a 40% reduction in average error in controlled environments and a 67% reduction in semi-controlled environments compared to existing approaches.
- The interpolated LIDAR data fusion maintained broad coverage similar to stereo cameras.
- Evaluation in unstructured terrain confirmed the method's significant corrective impact on topography estimation.
Conclusions:
- Interpolating LIDAR data before sensor fusion substantially improves the accuracy of stereo camera-based topography estimation.
- The developed method effectively extends LIDAR's accuracy benefits over larger areas, enhancing autonomous navigation capabilities.
- This approach offers a practical solution for more reliable off-road navigation systems.
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