Optimization Methods Applied to Motion Planning of Unmanned Aerial Vehicles: A Review

Israr, Amber; Ali, Zain Anwar; Alkhammash, Eman H.; Jussila, Jari

doi:10.3390/drones6050126

Cited by 35 publications

(22 citation statements)

References 86 publications

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“…We discussed limitations of UAVs in previous papers that include challenges of control, path planning, obstacle detection and avoidance, navigation and guidance, and others [38]. In this paper, various restricted capacity issues are discussed that hinder the performance of UAVs in larger fields of Rosaceae fruits.…”

Section: Capacity Limitations Of Uav Components That Restrict Flyingmentioning

confidence: 99%

A Comprehensive Review of Scab Disease Detection on Rosaceae Family Fruits via UAV Imagery

Ali

Yang

Israr

et al. 2023

Drones

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Disease detection in plants is essential for food security and economic stability. Unmanned aerial vehicle (UAV) imagery and artificial intelligence (AI) are valuable tools for it. The purpose of this review is to gather several methods used by our peers recently, hoping to provide some knowledge and assistance for researchers and farmers so that they can employ these technologies more advantageously. The studies reviewed in this paper focused on Scab detection in Rosaceae family fruits. Feature extraction, segmentation, and classification methods for processing the UAV-obtained images and detecting the diseases are discussed briefly. The advantages and limitations of diverse kinds of UAVs and imaging sensors are also explained. The widely applied methods for image analysis are machine learning (ML)-based models, and the extensively used UAV platforms are rotary-wing UAVs. Recent technologies that cope with challenges related to disease detection using UAV imagery are also detailed in this paper. Some challenging issues such as higher costs, limited batteries and flying time, huge and complex data, low resolution, and noisy images, etc., still require future consideration. The prime significance of this paper is to promote automation and user-friendly technologies in Scab detection.

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Section: Capacity Limitations Of Uav Components That Restrict Flyingmentioning

confidence: 99%

A Comprehensive Review of Scab Disease Detection on Rosaceae Family Fruits via UAV Imagery

Ali

Yang

Israr

et al. 2023

Drones

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“…Iran, Turkey, and India are also attempting efforts to mature and proliferate this technology using distributed intelligence and edge computing. Swarms of UAVs are the future of aerial wars, and the future is now [17].…”

Section: State-of-the-artmentioning

confidence: 99%

Motion Planning of UAV Swarm: Recent Challenges and Approaches

Iqbal¹,

Ali²,

Khan³

et al. 2022

Aeronautics - New Advances

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The unmanned aerial vehicle (UAV) swarm is gaining massive interest for researchers as it has huge significance over a single UAV. Many studies focus only on a few challenges of this complex multidisciplinary group. Most of them have certain limitations. This paper aims to recognize and arrange relevant research for evaluating motion planning techniques and models for a swarm from the viewpoint of control, path planning, architecture, communication, monitoring and tracking, and safety issues. Then, a state-of-the-art understanding of the UAV swarm and an overview of swarm intelligence (SI) are provided in this research. Multiple challenges are considered, and some approaches are presented. Findings show that swarm intelligence is leading in this era and is the most significant approach for UAV swarm that offers distinct contributions in different environments. This integration of studies will serve as a basis for knowledge concerning swarm, create guidelines for motion planning issues, and strengthens support for existing methods. Moreover, this paper possesses the capacity to engender new strategies that can serve as the grounds for future work.

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“…One of the technologies that have become humanassisted is the robot, which is utilized in various industries, including the military, the civilian sector, the medical field, aerospace, and agriculture [1]. Unmanned aerial vehicles (UAVs) are the most widely utilized flying robots because of their costeffectiveness, small size, lightweight, and portability [2]. Several companies around the world, including Amazon, Walmart, DHL, and Zookal, which invested in drone research for a variety of purposes, including freight and package delivery to consumers, have lately revealed the use of drones for commercial purpose [3].…”

Section: Introductionmentioning

confidence: 99%

“…Several companies around the world, including Amazon, Walmart, DHL, and Zookal, which invested in drone research for a variety of purposes, including freight and package delivery to consumers, have lately revealed the use of drones for commercial purpose [3]. One of the primary aspects of the robot's transition from one location to another is to generate a path plan from the starting point to the target point and avoid collisions with obstacles [1][2][3][4]. The global path planner is one vehicle path planning system type, it uses a priori information from the road map to generate the optimal possible path from the starting point to the destination point [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Planning the Optimal 3D Quadcopter Trajectory Using a Delivery System-Based Hybrid Algorithm

2023

IJIES

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Path planning is one of the most crucial aspects of implementing unmanned aerial vehicle (UAV) missions. Therefore, it is essential to figure out the optimal path from the starting point to the target point in different scenarios. In this paper, we propose employing a hybrid algorithm, named FPA-GA, generated by combining the flower pollination algorithm (FPA) and genetic algorithm (GA), to find an optimum path in a real modern building's environment. In addition, a cubic polynomial algorithm via two points was proposed to make the route adequate and smooth. Because the GA has a good capability for exploring the search space, it is employed for exploration while the FPA and GA are employed to increase the exploitation capability in the proposed algorithm. Five different scenarios are utilized to evaluate FPA-GA's ability to find the optimal path in a variety of situations, and then the proposed algorithm's performance is compared with that of seven other algorithms: GA, FPA, bat algorithm (BA), particle swarm optimization (PSO), whale optimization algorithm (WOA), improved whale optimization algorithm (IWOA), and IWOA-PSO. The best path, the mean path length, the standard derivation, and the worst path length are the four parameters used to compress data. In all scenarios, the results demonstrate that FPA-GA is capable of locating the shortest and most collision-free paths, and the hybrid algorithm FPA-GA is always superior to other algorithms. The proposed algorithm provided the mean path length enhancement in all scenarios, where the maximum enhancement equals (33.6%), (23.1%), (55.5%), (29.8%), (50.5%), (53.9%), and (26.4%) compared with GA, FPA, BA, PSO, WOA, IWOA, and IWOA-PSO, respectively. On the other hand, the proposed algorithm is guaranteed to find the best path in all scenarios, where the standard deviation of FPA-GA is always less than that of other algorithms.

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Optimization Methods Applied to Motion Planning of Unmanned Aerial Vehicles: A Review

Cited by 35 publications

References 86 publications

A Comprehensive Review of Scab Disease Detection on Rosaceae Family Fruits via UAV Imagery

A Comprehensive Review of Scab Disease Detection on Rosaceae Family Fruits via UAV Imagery

Motion Planning of UAV Swarm: Recent Challenges and Approaches

Planning the Optimal 3D Quadcopter Trajectory Using a Delivery System-Based Hybrid Algorithm

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