DPoom is an indoor robot self-driving around the DGIST dormitory lobby. For its autonomous driving, such modules are essentially required.
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SLAM : Firstly, it must use SLAM to scan around the indoor terrain for creating a map. During self-driving, it is used for localization.
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path planning : It plans a efficient and safe path to the destination using SLAM created map.
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DAP : DPoom could drive along the provided path using DAP, which listening encoder and IMU (from OpenCR).
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autodrive.py integrates navigation modules such as GPP and motion planner (MORP).
integration.py integrates all required modules when autonomous driving. The gif below was recorded when we test the robot to autonomous driving in DGIST domitory lobby.
