A Practical Interlacing-Based Coverage Path Planning Method for Fixed-Wing UAV Photogrammetry in Convex Polygon Regions

Huang, Junhua; Fu, Wenxing; Luo, Shaobo; Wang, Chenxin; Zhang, Bo

doi:10.3390/aerospace9090521

Cited by 3 publications

(11 citation statements)

References 36 publications

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“…Many research studies have been conducted to resolve the path planning issues of UAVs in terms of complexity. In [ 41 , 42 ], the authors described different areas using different sweep courses to identify the best path. In addition, the use of back-and-forth arrangements to reduce the distance between sub-areas was further studied in [ 43 ].…”

Section: Preliminariesmentioning

confidence: 99%

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Poudel

Arafat

Moh

2023

Sensors

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Advancements in electronics and software have enabled the rapid development of unmanned aerial vehicles (UAVs) and UAV-assisted applications. Although the mobility of UAVs allows for flexible deployment of networks, it introduces challenges regarding throughput, delay, cost, and energy. Therefore, path planning is an important aspect of UAV communications. Bio-inspired algorithms rely on the inspiration and principles of the biological evolution of nature to achieve robust survival techniques. However, the issues have many nonlinear constraints, which pose a number of problems such as time restrictions and high dimensionality. Recent trends tend to employ bio-inspired optimization algorithms, which are a potential method for handling difficult optimization problems, to address the issues associated with standard optimization algorithms. Focusing on these points, we investigate various bio-inspired algorithms for UAV path planning over the past decade. To the best of our knowledge, no survey on existing bio-inspired algorithms for UAV path planning has been reported in the literature. In this study, we investigate the prevailing bio-inspired algorithms extensively from the perspective of key features, working principles, advantages, and limitations. Subsequently, path planning algorithms are compared with each other in terms of their major features, characteristics, and performance factors. Furthermore, the challenges and future research trends in UAV path planning are summarized and discussed.

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Section: Preliminariesmentioning

confidence: 99%

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Poudel

Arafat

Moh

2023

Sensors

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“…Due to the great length of the Galician coastline (more than 1500 km [24]) and the short time of low tides for data collection, this work proposes the use of a small fixed-wind electric UAV for this type of operation. Small fixed-wing UAVs are relatively easy to transport and assemble; they can also carry larger payloads and reach higher speeds and flight ranges [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

“…The CPP allows to explore all the locations in a region of interest, considering vehicle restrictions, sensor characteristics and avoiding obstacles [25,27,[33][34][35][36]. The CPP is a task that has had multiple applications in robotics for a long time, like vacuum cleaner robots, lawn mowers, painting robots, demining, and agriculture [35,36], among many others.…”

Section: Introductionmentioning

confidence: 99%

“…In [36], it is implemented for optimal coverage in a port environment. In [27], CPP is used in photogrammetry tasks with a fixed-wing UAV, where turning radius constraints are considered. Turning constraints in fixed-wing CPP problems are also studied in [26,33,37,38].…”

Section: Introductionmentioning

confidence: 99%

“…Heuristic algorithms are based on simple rules and random approaches that define UAV behavior and, despite not guaranteeing full coverage, they may have some advantages in search or exploration applications from a cost/benefit point of view [25,35,40]. Complete algorithms are usually based on the decomposition of the area of interest into polygonal subregions called cells [25,27,35,37]. This decomposition can be (i) exact if the re-union of the cells forms the original region [33,36,38,[41][42][43] or (ii) approximate (also called grid-based) [25,27,34,35].…”

Section: Introductionmentioning

confidence: 99%

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A Benchmarking of Commercial Small Fixed-Wing Electric UAVs and RGB Cameras for Photogrammetry Monitoring in Intertidal Multi-Regions

Fontenla-Carrera,

Aldao,

Veiga

et al. 2023

Drones

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Small fixed-wing electric Unmanned Aerial Vehicles (UAVs) are perfect candidates to perform tasks in wide areas, such as photogrammetry, surveillance, monitoring, or search and rescue, among others. They are easy to transport and assemble, have much greater range and autonomy, and reach higher speeds than rotatory-wing UAVs. Aiming to contribute towards their future implementation, the objective of this article is to benchmark commercial, small, fixed-wing, electric UAVs and compatible RGB cameras to find the best combination for photogrammetry and data acquisition of mussel seeds and goose barnacles in a multi-region intertidal zone of the south coast of Galicia (NW of Spain). To compare all the options, a Coverage Path Planning (CPP) algorithm enhanced for fixed-wing UAVs to cover long areas with sharp corners was posed, followed by a Traveling Salesman Problem (TSP) to find the best route between regions. Results show that two options stand out from the rest: the Delair DT26 Open Payload with a PhaseOne iXM-100 camera (shortest path, minimum number of pictures and turns) and the Heliplane LRS 340 PRO with the Sony Alpha 7R IV sensor, finishing the task in the minimum time.

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Path Planning of Multiple Unmanned Aerial Vehicles Covering Multiple Regions Based on Minimum Consumption Ratio

et al. 2023

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Investigating the path planning of multiple unmanned aerial vehicles (UAVs) covering multiple regions, this work proposes an effective heuristic method of region coverage path planning to reduce the complexity of the problem. The proposed method decomposes the solution process into two stages. First of all, the two most important parameters affecting the performance of UAV missions were considered, namely, the flying speed and the scan width. According to these two parameters of UAVs, a new multi-regional allocation scheme based on the minimum consumption ratio was proposed. With this allocation scheme, the coverage task allocation and path pre-planning of UAVs were obtained. Then, the UAVs’ trajectory routes were optimized based on the dynamic planning algorithm to reduce the time consumption of UAVs on the transfer path between regions. The method was evaluated with numerical experiments. The results showed that the proposed method can effectively solve the path planning problem of multiple UAVs covering multiple regions. Compared with an advanced algorithm, the time consumption for homogeneous and heterogenous UAV performance was reduced by 5.1% and 3%, respectively.

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A Practical Interlacing-Based Coverage Path Planning Method for Fixed-Wing UAV Photogrammetry in Convex Polygon Regions

Cited by 3 publications

References 36 publications

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

A Benchmarking of Commercial Small Fixed-Wing Electric UAVs and RGB Cameras for Photogrammetry Monitoring in Intertidal Multi-Regions

Path Planning of Multiple Unmanned Aerial Vehicles Covering Multiple Regions Based on Minimum Consumption Ratio

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