Improving particle swarm optimization path planning through inclusion of flight mechanics

Holub, Joseph

doi:10.31274/etd-180810-1925

Cited by 2 publications

(2 citation statements)

References 40 publications

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“…The segment distance is the straight-line distance between two turning points. This distance should be long enough to ensure that an aircraft completes a turn smoothly [28]. Therefore, for a normal flight, the distance between two turning points must exceed 7:4 km, and the turning radius must exceed 3:7 km.…”

Section: Segment Distancementioning

confidence: 99%

Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather

Qiu

Jin

et al. 2022

International Journal of Aerospace Engineering

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Hazardous weather has become a major cause of flight delays in recent years. With the development of satellite navigation systems, the study of flight-path optimization under hazardous weather conditions has become especially important. In this study, radar data were used as the basis for the initial flight-restricted area under hazardous weather conditions, and the Graham algorithm was used to delineate the dynamic flight-restricted area by comprehensively considering the hazardous weather boundary changes along with the speed and direction. Then, under the grid environment model, the range of influence, size, and distribution characteristics of the flight-restricted area was examined, and the path optimization model was created according to constraints related to the path distance, corner size, and number of turning points. An improved F-RRT ∗ algorithm was developed to solve the model. The algorithm can overcome the problems of traditional path planning algorithms, such as strong randomness, poor guidance, slow convergence speed, unsmooth paths, and poor tracing smoothness. Finally, a simulation analysis was conducted on the Guiyang–Guangzhou route in China as an example. This study can address the drawbacks of existing research on route change and provide sufficient theoretical support and reference for the implementation of specific route change plans in the future.

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Section: Segment Distancementioning

confidence: 99%

Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather

Qiu

Jin

et al. 2022

International Journal of Aerospace Engineering

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“…Genetic algorithms have been used to trace flight paths [15], and the use of ant colony algorithms for 3D route planning has also been considered [17]. UAV path planning using Particle Swarm Optimization and digital pheromones incorporating vehicle mechanics to generate multiple 3-d paths for operators have been proposed [24], as have optimization algorithms for multiobjective drone route planning [32]. Fast graph search algorithms that satisfy constraints on flights have been used to determine the optimum path of a drone traveling between two given locations [13] and UAV flight path planning in time-space varying wind fields using a kinematic tree path planner have been developed [12].…”

Section: Related Workmentioning

confidence: 99%

DIMPL: a distributed in-memory drone flight path builder system

Shukla¹,

Chen

2018

J Big Data

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As use of drones rapidly expands, it is aided by improvements in technology such as high speed cameras, sensors, and processors able to analyze the data rapidly and efficiently on the drone. Better scalability in processing image, terrain, weather and surface data and using it to aid in navigation has also allowed them to become increasingly autonomous during flight. Drones have proven very useful in both military battlefield and civilian tasks. Along with common civilian tasks in education [30], studying natural phenomena [45], reconnaissance [36] and conservation [28] they have been used increasingly in surveying farms [41], forests [10] and borders [27]. Drones can either be controlled manually by an operator or fly autonomously, but as the use for an operator increases the cost considerably, it is clearly preferable for them to operate autonomously. Autonomous flight presents challenges in terrain navigation, however, as a multitude of flight path scenarios such as variations in altitude and the density of objects to be surveyed must be taken into account. Flight planning

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Improving particle swarm optimization path planning through inclusion of flight mechanics

Cited by 2 publications

References 40 publications

Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather

Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather

DIMPL: a distributed in-memory drone flight path builder system

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Improving particle swarm optimization path planning through inclusion of flight mechanics

Cited by 2 publications

References 40 publications

Improved F-RRT ∗ Algorithm for Flight-Path Optimization in Hazardous Weather

Improved F-RRT ∗ Algorithm for Flight-Path Optimization in Hazardous Weather

DIMPL: a distributed in-memory drone flight path builder system

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Product

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Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather

Improved F-RRT $^{*}$ Algorithm for Flight-Path Optimization in Hazardous Weather