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Quadrotor path planning using A* search algorithm and minimum snap trajectory generation

Youkyung Hong, Suseong Kim, Yookyung Kim, Jihun Cha

2021ETRI Journal20 citationsDOIOpen Access PDF

Abstract

In this study, we propose a practical path planning method that combines the A* search algorithm and minimum snap trajectory generation. The A* search algorithm determines a set of waypoints to avoid collisions with surrounding obstacles from a starting to a destination point. Only essential waypoints (waypoints necessary to generate smooth trajectories) are extracted from the waypoints determined by the A* search algorithm, and an appropriate time between two adjacent waypoints is allocated. The waypoints so determined are connected by a smooth minimum snap trajectory, a dynamically executable trajectory for the quadrotor. If the generated trajectory is invalid, we methodically determine when intermediate waypoints are needed and how to insert the points to modify the trajectory. We verified the performance of the proposed method by various simulation experiments and a real-world experiment in a forested outdoor environment.

Topics & Concepts

TrajectoryPath (computing)ExecutableSet (abstract data type)AlgorithmPoint (geometry)Start pointComputer scienceSearch algorithmMotion planningMathematical optimizationMathematicsRobotArtificial intelligencePhysicsGeometryOperating systemProgramming languageAstronomyRobotic Path Planning AlgorithmsRobotics and Sensor-Based LocalizationControl and Dynamics of Mobile Robots
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