Project Objective
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Develop real-time position estimation and 3D map generation algorithm for unmanned vehicles traveling in the wilderness environment based on lidar, camera, and IMU sensor fusion data
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Develop an algorithm that generates location information along with object recognition and classification information by learning from existing datasets in various environments.
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Developed algorithms to convert camera-based recognition/classification information into 3D location information based on calibration information of camera and lidar sensors
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Verified performance through interworking with previously developed unmanned vehicles
Contributions
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Investigated, compared, selected, analyzed, and implemented lidar-based location estimation algorithm
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Investigated, compared, selected, and analyzed camera-based position estimation algorithms
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Implemented multi-sensor fusion module
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Factor graph-based sensor fusion → To improve the quality of mapping results
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Kalman filter-based sensor fusion → To improve the speed of Localization results
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Implement obstacle occupancy grid mapping module
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Analyzed the results and created a user manual