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Robust and Efficient Quadrotor Trajectory Generation for Fast Autonomous Flight

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In this paper, we propose a robust and efficient quadrotor motion planning system for fast flight in 3-D complex environments. We adopt a kinodynamic path searching method to find a safe, kinodynamic feasible and minimum-time initial trajectory in the discretized control space. We improve the smoothness and clearance of the trajectory by a B-spline optimization, which incorporates gradient information from a Euclidean distance field (EDF) and dynamic constraints efficiently utilizing the convex hull property of B-spline. Finally, by representing the final trajectory as a non-uniform B-spline, an iterative time adjustment method is adopted to guarantee dynamically feasible and non-conservative trajectories. We validate our proposed method in various complex simulational environments. The competence of the method is also validated in challenging real-world tasks. We release our code as an open-source package.

Boyu Zhou, Fei Gao, Luqi Wang, Chuhao Liu, Shaojie Shen• 2019

Related benchmarks

TaskDatasetResultRank
Autonomous UAV Trajectory PlanningSimulated Environment 0 obs./m2
Average Flight Time15.39
4
Autonomous Flight PlanningSimulated Environment 0 obs/m^2 50x50x3 m^3 volume (obstacle-free)
Avg. Planning Iterations25
4
Autonomous UAV Trajectory PlanningSimulated Environment 0.05 obs./m2
Average Flight Time17.51
4
Autonomous UAV Trajectory PlanningSimulated Environment 0.1 obs./m2
Avg Flight Time18.2
4
Autonomous Flight PlanningSimulated Environment 0.05 obs/m^2 50x50x3 m^3 volume (sparsely obstructed)
Average Planning Iterations29.9
4
Autonomous Flight PlanningSimulated Environment 0.1 obs/m^2 moderately cluttered 50x50x3 m^3 volume
Avg Planning Iterations32.7
4
Autonomous Flight PlanningSimulated Environment 0.2 obs/m^2 50x50x3 m^3 volume (densely cluttered)
Average Number of Planning Iterations40.9
4
Autonomous UAV Trajectory PlanningSimulated Environment 0.2 obs./m2
Avg Flight Time (s)20.97
4
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