Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence
Unmanned autonomous helicopter (UAH) path planning problem is an important component of the UAH mission planning system. The performance of the automatic path planner determines the quality of the UAH flight path. Aiming to produce a high-quality flight path, a path planning system is designed based...
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Series: | Neural Plasticity |
Online Access: | http://dx.doi.org/10.1155/2021/6639664 |
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doaj-9afa23fc3b994865b3236a72f812f6df2021-02-15T12:53:10ZengHindawi LimitedNeural Plasticity2090-59041687-54432021-01-01202110.1155/2021/66396646639664Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented IntelligenceZengliang Han0Mou Chen1Tongle Zhou2Zhiqiang Nie3Qingxian Wu4College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaScience and Technology on Electro-optic Control Laboratory, Luoyang Institute of Electro-Optical Equipment of Avic, Luoyang 471000, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, ChinaUnmanned autonomous helicopter (UAH) path planning problem is an important component of the UAH mission planning system. The performance of the automatic path planner determines the quality of the UAH flight path. Aiming to produce a high-quality flight path, a path planning system is designed based on human-computer hybrid augmented intelligence framework for the UAH in this paper. Firstly, an improved artificial bee colony (I-ABC) algorithm is proposed based on the dynamic evaluation selection strategy and the complex optimization method. In the I-ABC algorithm, the following way of on-looker bees and the update strategy of nectar source are optimized to accelerate the convergence rate and retain the exploration ability of the population. In addition, a space clipping operation is proposed based on the attention mechanism for constructing a new spatial search area. The search time can be further reduced by the space clipping operation under the path planning result within acceptable changes. Moreover, the entire optimization process and results can be feeded back to the knowledge database by the human-computer hybrid augmented intelligence framework to guide subsequent path planning issues. Finally, the simulation results confirm that a feasible and effective flight path can be quickly generated by the UAH path planning system based on human-computer hybrid augmented intelligence.http://dx.doi.org/10.1155/2021/6639664 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zengliang Han Mou Chen Tongle Zhou Zhiqiang Nie Qingxian Wu |
spellingShingle |
Zengliang Han Mou Chen Tongle Zhou Zhiqiang Nie Qingxian Wu Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence Neural Plasticity |
author_facet |
Zengliang Han Mou Chen Tongle Zhou Zhiqiang Nie Qingxian Wu |
author_sort |
Zengliang Han |
title |
Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence |
title_short |
Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence |
title_full |
Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence |
title_fullStr |
Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence |
title_full_unstemmed |
Path Planning of Unmanned Autonomous Helicopter Based on Human-Computer Hybrid Augmented Intelligence |
title_sort |
path planning of unmanned autonomous helicopter based on human-computer hybrid augmented intelligence |
publisher |
Hindawi Limited |
series |
Neural Plasticity |
issn |
2090-5904 1687-5443 |
publishDate |
2021-01-01 |
description |
Unmanned autonomous helicopter (UAH) path planning problem is an important component of the UAH mission planning system. The performance of the automatic path planner determines the quality of the UAH flight path. Aiming to produce a high-quality flight path, a path planning system is designed based on human-computer hybrid augmented intelligence framework for the UAH in this paper. Firstly, an improved artificial bee colony (I-ABC) algorithm is proposed based on the dynamic evaluation selection strategy and the complex optimization method. In the I-ABC algorithm, the following way of on-looker bees and the update strategy of nectar source are optimized to accelerate the convergence rate and retain the exploration ability of the population. In addition, a space clipping operation is proposed based on the attention mechanism for constructing a new spatial search area. The search time can be further reduced by the space clipping operation under the path planning result within acceptable changes. Moreover, the entire optimization process and results can be feeded back to the knowledge database by the human-computer hybrid augmented intelligence framework to guide subsequent path planning issues. Finally, the simulation results confirm that a feasible and effective flight path can be quickly generated by the UAH path planning system based on human-computer hybrid augmented intelligence. |
url |
http://dx.doi.org/10.1155/2021/6639664 |
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