Path Generation Method of UAV Autopilots using Max-Min Algorithm
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초록
In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has foundwidespread application across a diverse range of fields and is also utilized for controlling unmanned aerialvehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult forthe user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs aflight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally flystraight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVsmay collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust thegenerated path taking the locations of the obstacles into consideration. This paper proposes a natural pathgeneration method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, theproposed method generates paths that allow UAVs to avoid obstacles.
Abstract
In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has foundwidespread application across a diverse range of fields and is also utilized for controlling unmanned aerialvehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult forthe user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs aflight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally flystraight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVsmay collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust thegenerated path taking the locations of the obstacles into consideration. This paper proposes a natural pathgeneration method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, theproposed method generates paths that allow UAVs to avoid obstacles.
참고문헌 (11)
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