Development of Path Planning Tool for Unmanned System Considering Energy Consumption

Jung, Sunghun

doi:10.3390/app9163341

Cited by 4 publications

(3 citation statements)

References 16 publications

(18 reference statements)

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“…The drone route should also be straight that, on the one hand, it will reduce the energy consumption of the equipment and, to some extent, prevent the device from rocking, which would negatively affect the collected material [34][35][36]. A unique way to plan a drone flight route was presented by Sunghun Jung [37], in which he showed an algorithm that provides a flight path with low electricity consumption. Ultimately, to limit any human interference, we recommend installing a permanent UAV nest near the bridge, from which the drone would take off and in which it could recharge a battery.…”

Section: Essentialsmentioning

confidence: 99%

Framework for Structural Health Monitoring of Steel Bridges by Computer Vision

Marchewka

Ziółkowski

Aguilar

2020

Sensors

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The monitoring of a structural condition of steel bridges is an important issue. Good condition of infrastructure facilities ensures the safety and economic well-being of society. At the same time, due to the continuous development, rising wealth of the society and socio-economic integration of countries, the number of infrastructural objects is growing. Therefore, there is a need to introduce an easy-to-use and relatively low-cost method of bridge diagnostics. We can achieve these benefits by the use of Unmanned Aerial Vehicle-Based Remote Sensing and Digital Image Processing. In our study, we present a state-of-the-art framework for Structural Health Monitoring of steel bridges that involves literature review on steel bridges health monitoring, drone route planning, image acquisition, identification of visual markers that may indicate a poor condition of the structure and determining the scope of applicability. The presented framework of image processing procedure is suitable for diagnostics of steel truss riveted bridges. In our considerations, we used photographic documentation of the Fitzpatrick Bridge located in Tallassee, Alabama, USA.

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Section: Essentialsmentioning

confidence: 99%

Framework for Structural Health Monitoring of Steel Bridges by Computer Vision

Marchewka

Ziółkowski

Aguilar

2020

Sensors

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“…There are six papers focused on the UAV path planning technology [13][14][15][16][17][18]. F. Yan, X. Zhu, Z. Zhou, and J. Chu present an empirical hierarchical mission planning to decouple and solve the simultaneous arrival of a multi-UAV coalition problem [13].…”

Section: Advanced Uav Technologiesmentioning

confidence: 99%

“…Z. Shao, F. Yan, Z. Zhou, and X. Zhu present the distributed cooperative particle swarm optimization (DCPSO) algorithm with an elite keeping strategy to generate a safe flyable path of a single UAV in the multi-UAV rendezvous mission [15]. S. Jung presents the energy-efficient path planning by considering the distance between waypoint nodes, the minimum and maximum speed of the UAV, the weight of the UAV, and the angle between two intersection edges [16]. M. Zhu, X. Zhang, H. Luo, G. Wang, and B. Zhang present step by step optimization processes to achieve the safe shortest Dubins path using a multi-UAV rapid-assessment routing problem (MURARP) by considering the multi-depot revisit-allowed Dubins team orienteering problem (TOP) with variable profit [17].…”

Section: Advanced Uav Technologiesmentioning

confidence: 99%

Special Issue on Unmanned Aerial Vehicles (UAVs)

Jung

2020

Applied Sciences

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This editorial paper was a special issue of Applied Sciences belonging to the section of mechanical engineering in MDPI journal and summarized the collected manuscripts regarding the unmanned aerial vehicles (UAVs) related technologies, including communication, control, collision avoidance, modeling, path planning, human-machine interface (HMI), artificial intelligence (AI), etc. Chronologically, this special issue was started to be coordinated at the end of Oct 2018, prepared for a month and opened to collect manuscripts from the middle of Nov 2018 until the end of Dec 2019. During almost a year, 26 papers were published online out of 50 submitted papers which results in 52% acceptance rate.

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Energy Efficient Path Planning Scheme for Unmanned Aerial Vehicle Using Hybrid Generic Algorithm-Based Q-Learning Optimization

Saeed,

Ali,

Abdelhaq

et al. 2024

IEEE Access

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Efficient path planning optimization strategies are required to maximize flying time while consuming the least energy. This research offers a novel approach for energy-efficient path planning for Unmanned Aerial Vehicles (UAVs) that combines a hybrid evolutionary algorithm and Q-learning while accounting for the UAV's velocity and distance from obstacles. To overcome the constraints of traditional optimization approaches, the hybrid methodology combines genetic algorithms and Q-learning. The suggested approach optimizes path-planning decisions based on realtime information by considering the UAV's velocity and distance from obstacles. Genetic Algorithm (GA) creates a wide collection of candidate pathways. In contrast, Q-learning uses reinforcement learning to make educated selections based on the UAV's present velocity and proximity to static obstacles. This integration allows the UAV to modify its path dynamically based on its energy requirements and environmental constraints. The main goal is to develop a UAV path planning scheme capable of dealing with obstacle-filled environments to improve energy efficiency and collision avoidance during flight missions. Our experimental results show that the hybrid technique outperforms the classical GA method in terms of energy efficiency by significantly reducing energy consumption while maintaining a suitable collision rate and the best path cost to the desired locations. The analysis results improve the performance of the hybrid GA/QL algorithm by more than 57.14% compared to classical GA.

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Development of Path Planning Tool for Unmanned System Considering Energy Consumption

Cited by 4 publications

References 16 publications

Framework for Structural Health Monitoring of Steel Bridges by Computer Vision

Framework for Structural Health Monitoring of Steel Bridges by Computer Vision

Special Issue on Unmanned Aerial Vehicles (UAVs)

Energy Efficient Path Planning Scheme for Unmanned Aerial Vehicle Using Hybrid Generic Algorithm-Based Q-Learning Optimization

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