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Semantic SLAM in a forest environment

  • The Goal of the project is to enable autonomous navigation of an autonomous UAV in a forest environment to allow UAV and UGV robot teams to identify and eliminate potential triggers of forest fires

  • Implemented Simultaneous localization and mapping algorithm that utilizes semantic information to enable autonomous navigation of drones

  • The algorithm utilizes the semantically segmented point cloud and recursively estimates the Diameter at breast height (DBH) of surrounding trees by solving a geometric least squares problem and uses this information to localize the drone and also map the environment

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