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Multi-Objective Design and Path Planning Optimization of Unmanned Aerial Vehicles (UAVs)

机译:无人机的多目标设计和路径规划优化

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This paper presents the topic of combined UAV design and path planning using bi-objective optimization. Two optimization models, integrated and decomposed, are developed and solved for path planning and design optimization of UAVs. Both models minimize a weighted sum of risk and time. The risk is based on a simulation of a UAV's crash after it loses power and is estimated by computing an expected number of on-the-ground human population fatalities which are located at or near the UAV crash site. The flight time is computed for the UAV as it travels from a start to an end point. The integrated model solves the design and path planning optimization problem all-at-once. The decomposed model has two subproblems: one for the design optimization of UAV and another for its path planning optimization. A new decomposed method for solving the path planning subproblem while considering the design optimization subproblem is presented, which solves the path planning subproblem for a discrete graph. Results for this new method are compared to an integrated all-at-once approach that does not treat the design and path planning subproblems separately, which can indicate the method proposed is less vulnerable to local minima in the path planning optimization subproblem.
机译:本文提出了使用双目标优化的组合无人机设计和路径规划的主题。针对无人机的路径规划和设计优化,开发并求解了两种集成和分解的优化模型。两种模型都将风险和时间的加权总和最小化。该风险基于对无人机失去动力后的坠机进行的仿真,并通过计算位于无人机坠毁地点或附近的地面上人口死亡的预期数量进行估算。计算无人机从起点到终点的飞行时间。集成模型一次解决了设计和路径规划优化问题。分解后的模型有两个子问题:一个用于无人机的设计优化,另一个用于路径规划的优化。提出了一种在考虑设计优化子问题的同时解决路径规划子问题的新方法,该方法解决了离散图的路径规划子问题。将该新方法的结果与不单独处理设计和路径规划子问题的集成式一次性解决方案进行了比较,这可以表明所提出的方法在路径规划优化子问题中较不容易受到局部极小值的影响。

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