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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Main Authors: Zengliang Han, Mou Chen, Tongle Zhou, Zhiqiang Nie, Qingxian Wu
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Neural Plasticity
Online Access:http://dx.doi.org/10.1155/2021/6639664
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spelling 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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AT mouchen pathplanningofunmannedautonomoushelicopterbasedonhumancomputerhybridaugmentedintelligence
AT tonglezhou pathplanningofunmannedautonomoushelicopterbasedonhumancomputerhybridaugmentedintelligence
AT zhiqiangnie pathplanningofunmannedautonomoushelicopterbasedonhumancomputerhybridaugmentedintelligence
AT qingxianwu pathplanningofunmannedautonomoushelicopterbasedonhumancomputerhybridaugmentedintelligence
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