Adaptive Operator Quantum-Behaved Pigeon-Inspired Optimization Algorithm with Application to UAV Path Planning

Hu, Chunhe; Xia, Yu; Zhang, Junguo

doi:10.3390/a12010003

Cited by 28 publications

(19 citation statements)

References 39 publications

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“…The test function set I choose is the CEC-2015 data set and the CEC-2017 data set. These ten algorithms are as follows: Particle swarm Optimization (PSO) [23], Whale Optimization Algorithm (WOA) [24], Grey Wolf Optimizer (GWO), Tunicate Swarm Algorithm (TSA) [25], Butterfly Optimization Algorithm (BOA) [26], Satin bowerbird Optimization (SBO) [27], Pigeon Inspired Optimization (PIO) [28]…”

Section: Test Of Cec-2015 and Cec-2017 Test Functionsmentioning

confidence: 99%

A Hybrid Sparrow Search Algorithm Based on Constructing Similarity

Liu

Wang

2021

IEEE Access

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Sparrow search algorithm (SSA) is easy to fall into local convergence and convergence stagnation. In order to solve these problems, this paper introduced Circle chaos map into the original SSA to improve its global search ability at the beginning of iteration. Meanwhile, it introduced T-distribution variation to affect the sparrow population position update rules in different iteration periods. Finally, we constructed the ''similarity function'' to measure the ''dispersion'' of the sparrow population, and formulated the search rules of the sparrow population under different ''dispersion''. In order to test the specific optimization performance of the proposed algorithm, the test results of 54 test functions are compared with those of 9 other algorithms which are widely used, and then the test results are analyzed using non-parametric tests in statistics. At the same time, this paper introduces this algorithm into three concrete engineering test problems for testing. The results of these tests all prove that the proposed algorithm has stronger global optimization ability and higher convergence precision compared with other algorithms.

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Section: Test Of Cec-2015 and Cec-2017 Test Functionsmentioning

confidence: 99%

A Hybrid Sparrow Search Algorithm Based on Constructing Similarity

Liu

Wang

2021

IEEE Access

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“…The UAV flight route should not run above the road, so that in the event of a breakdown, it does not fall onto the road surface and cause an accident. 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.…”

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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“…Associated to the coordination and path planning of fixed number of UAVs of a few UAVs Hu et al 17 Improved QPIO mechanism with addition of logical map, adding parameters, and a centralized update mechanism.…”

Section: Lacks Introduction Of Real Environment Flight Testing Constraintsmentioning

confidence: 99%

Aspects of unmanned aerial vehicles path planning: Overview and applications

Khan

Saad

et al. 2021

Int J Communication

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Aiming to the applications from security surveillance, military operational capabilities to the content and package delivery, unmanned aerial vehicles (UAVs) has a successfully created his space in the available technologies. The compact sized powerful flying robots are wirelessly controlled and are capable to complete tasks with and without direct human intervention. UAVs however still face serious challenges that limit the dream of complete autonomous unmanned flying machines. The key challenges include path planning and obstacle avoidance of these unmanned flying robots that are unavoidable while performing the application-specific functionalities both in indoor and outdoor environments. In this manuscript with a survey, we investigate the state-of-the-art UAV path planning algorithms and obstacle avoidance techniques. We have also summarized and compared the schemes in tabular form. In addition, current and future research directions and challenges are also discussed, showing the prospective research directions.

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Adaptive Operator Quantum-Behaved Pigeon-Inspired Optimization Algorithm with Application to UAV Path Planning

Cited by 28 publications

References 39 publications

A Hybrid Sparrow Search Algorithm Based on Constructing Similarity

A Hybrid Sparrow Search Algorithm Based on Constructing Similarity

Framework for Structural Health Monitoring of Steel Bridges by Computer Vision

Aspects of unmanned aerial vehicles path planning: Overview and applications

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