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.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    21
    References
    0
    Citations
    NaN
    KQI
    []