3D UAV Path Planning Using Global-Best Brain Storm Optimization Algorithm and Artificial Potential Field
2019
In this paper, the online obstacle avoidance path planning problem for UAV is studied. The global-best brain storming algorithm (GBSO) and artificial potential field (APF) method are applied to UAV path planning. The global-best brain storm optimization algorithm is applied for avoiding with fixed obstacles, which knowing at path planning stage. The pre-planning path can be obtained by the GBSO. When the sensors carried by the UAV identify the accidental obstacle during flight, the local path re-planning mechanism is triggered. In the re-plan stage, the artificial potential field method is applied for finding path with collision avoidance. The cubic B-spline curve is adopted for UAV 3D path planning. The maximum curvature and climb (or dive) angle constraints of path are taken into consideration in pre-planning stage. The simulation results demonstrate that the effectiveness of the proposed method for online UAV 3D path planning problem.
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