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基于遗传算法和贪婪策略的重载半刚性飞艇多点任务路径规划。

Genetic Algorithm and Greedy Strategy-Based Multi-Mission-Point Route Planning for Heavy-Duty Semi-Rigid Airship.

机构信息

School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.

Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China.

出版信息

Sensors (Basel). 2022 Jun 30;22(13):4954. doi: 10.3390/s22134954.

Abstract

The large volume and windward area of the heavy-duty semi-rigid airship (HSA) result in a large turning radius when the HSA passes through every mission point. In this study, a multi-mission-point route planning method for HSA based on the genetic algorithm and greedy strategy is proposed to direct the HSA maneuver through every mission point along the optimal route. Firstly, according to the minimum flight speed and the maximum turning slope angle of the HSA during turning, the minimum turning radius of the HSA near each mission point is determined. Secondly, the genetic algorithm is used to determine the optimal flight sequence of the HSA from the take-off point through all the mission points to the landing point. Thirdly, based on the optimal flight sequence, the shortest route between every two adjacent mission points is obtained by using the route planning method based on the greedy strategy. By determining the optimal flight sequence and the shortest route, the optimal route for the HSA to pass through all mission points can be obtained. The experimental results show that the method proposed in this study can generate the optimal route with various conditions of the mission points using simulation studies. This method reduces the total voyage distance of the optimal route by 18.60% on average and improves the flight efficiency of the HSA.

摘要

重载半刚性飞艇(HSA)体积大、迎风面积大,导致 HSA 通过每个任务点时转弯半径较大。在这项研究中,提出了一种基于遗传算法和贪婪策略的 HSA 多任务点路径规划方法,以指导 HSA 沿着最优路径通过每个任务点进行机动。首先,根据 HSA 在转弯过程中的最小飞行速度和最大转弯坡度角,确定 HSA 在每个任务点附近的最小转弯半径。其次,利用遗传算法确定 HSA 从起飞点到所有任务点再到降落点的最优飞行序列。然后,基于最优飞行序列,通过基于贪婪策略的路径规划方法获得每两个相邻任务点之间的最短路径。通过确定最优飞行序列和最短路径,可以得到 HSA 通过所有任务点的最优路径。实验结果表明,该研究提出的方法可以通过仿真研究生成具有各种任务点条件的最优路径。该方法平均减少了最优路径的总航程 18.60%,提高了 HSA 的飞行效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9e25/9269712/1bc479a240e6/sensors-22-04954-g001.jpg

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