Study on UAV Path Planning Approach Based on Fuzzy Virtual Force

Zhang, Dong; Rulin, Zhang; Zong-ji, Chen; Zhou, Rui

doi:10.1016/s1000-9361(09)60225-9

Cited by 53 publications

(14 citation statements)

References 8 publications

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“…That is, global planning is conducted first by inputting the sensory information from planners and then conducting online preplanning once a previously unknown or unencountered obstacle is detected. Dong et al [112] proposed a new fuzzy virtual force method with a fixed step size to meet the online realtime requirements. Kermani and Afzalian [113] proposed an online path method based on GA, which meets the objectives of minimum distance, no collisions, maximum communication convergence and support of some no-fly zones.…”

Section: Path Searching Algorithmmentioning

confidence: 99%

Recent Research Progress of Unmanned Aerial Vehicle Regulation Policies and Technologies in Urban Low Altitude

et al. 2020

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With the rapid expansion in the number of Unmanned Aircraft Vehicles (UAVs) available and the development of modern technologies, the commercial applications of UAVs in urban areas, such as urban remote sensing (RS), express services, urban road traffic monitoring, urban police security, urban air shows and so on, have increased greatly. However, most UAVs, especially light and small civil UAVs, have been operating in low-altitude airspace, and a conflict may exist between increasing the number of UAVs and the limited low airspace. To promote low-altitude airspace resource development and to standardize the operation and management of UAVs in urban regions, some global laws and regulations and key technologies for urban low-altitude applications of UAVs have been implemented. This paper reviews the development of current policies and key technologies concerning safe and efficient operations of the light-and-small civil UAVs in low altitude in urban areas. Discussions are made progressively on measures and methods of airspace restriction, airspace structuring and air route planning in China primarily and the rest of world. After surveying the practical industry tests and the initial studies of air routes, the survey results indicate that the construction of air route networks is a scientific and effective measure to standardize and improve the efficiency of low-altitude UAV operations. From the view point of safety and efficiency, the most valuable direction for UAV regulation in urban regions involves deepening the research which largely relies on urban RS and Geographic Information System (GIS) technology, and application demonstrations of low-altitude public air route networks. INDEX TERMS Low-altitude airspace, RS and GIS for UAV regulation, UAV regulation technology and policy, Urban region, UAV low-altitude air routes.

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Section: Path Searching Algorithmmentioning

confidence: 99%

Recent Research Progress of Unmanned Aerial Vehicle Regulation Policies and Technologies in Urban Low Altitude

et al. 2020

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“…The FVF (Fuzzy Virtual Force) method is convenient and fast for UAV path planning. When the FVF method and the A* search algorithm are compared with each other, the FVF method is superior to the online UAV path planning in the complex environment [6]. Jinbae et al (2017) proposed an independent flight plan strategy for UAVs through reinforcement learning.…”

Section: General Literature Reviewmentioning

confidence: 99%

“…The standard route planning problem is to determine an ideal or time-based path between the required sites under certain restrictions. After planning the flight plan (unmanned aerial vehicles capable of entering enemy threats, perform certain tasks in the enemy's air defense zone and ensure their safety [6].…”

Section: Introductionmentioning

confidence: 99%

Path Planning Algorithms for Unmanned Aerial Vehicles

Dhulkefl¹,

Durdu²

2019

IJTSRD

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In this paper, the shortest path for Unmanned Aerıal Vehicles (UAVs) is calculated with two-dimensional (2D) path planning algorithms in the environment including obstacles and thus the robots could perform their tasks as soon as possible in the environment. The aim of this paper is to avoid obstacles and to find the shortest way to the target point. Th e simulation environment was created to evaluate the arrival time on the path planning algorithms (A* and Dijkstra algorithms) for the UAVs. As a result, real-time tests were performed with UAVs

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“…The other researcher combined virtual force fuzzy algorithm with graph theory as conducted by Zhuoning et al, [12]. Graph theory is used to create a 2-dimensional environment map by dividing the map into small grids and then the fuzzy algorithm used to get to the goal position and avoid obstacles is identified.…”

Section: Introductionmentioning

confidence: 99%