Search

Your search keyword '"Han, Zengliang"' showing total 14 results
Start Over Author "Han, Zengliang"
14 results on '"Han, Zengliang"'

2. Path Planning of Unmanned Helicopter Based on an Improved Artificial Bee Colony Algorithm

Author

Han, Zengliang, Wu, Qingxian, Chen, Mou, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Yu, Xiang, editor

Published
2022
Full Text
View/download PDF

9. Path planning of unmanned autonomous helicopter based on improved wolf pack algorithm.

Author

WANG Liwen, SHAO Shuyi, WU Qingxian, and HAN Zengliang

Subjects
FLIGHT planning (Aeronautics), HELICOPTERS, WANDERING behavior, ALGORITHMS, GLOBAL optimization, SEARCHING behavior
Abstract

For the problems of traditional wolf pack algorithm (WPA) in the flight path planning for unmanned autonomous helicopters (UAH), including slower convergence speed and easy failing into local optimum solution, a three-dimensional flight path planning algorithm for UAH based on improved WPA is proposed. Firstly, the three-dimensional environment, constraints and fitness function of UAH flight are modeled. Secondly, the adaptive step-size method is used to improve the step size of the three main steps of wandering behavior, summoning behavior and siege behavior in the traditional WPA. At the same time, the strategy of combing Levy flight and changing direction migration are used for adjusting direction and scope of the search in walking behavior, so as to improve the global optimization ability and convergence speed of the algorithm. Finally, the simulation results show that the improved WPA has faster convergence and better track quality, which verifies the effectiveness of the proposed algorithm in the UAH flight path planning. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

11. Research of multi-AGV scheduling system based on a new mixed regional control model

Author

Dongqing Wang and Han Zengliang

Subjects
0209 industrial biotechnology, 021103 operations research, 020901 industrial engineering & automation, Computer science, Distributed computing, 0211 other engineering and technologies, 02 engineering and technology, Deadlock, Scheduling system, Scheduling (computing)
Abstract

In order to reduce the inherent defects and complexity of the multi-AGV system, a new guide-path configuration of mixed regional control module and its path scheduling is investigated. By a scheme of the shortest waiting time for the task, the efficiency of the system running time is achieved in the multi-AGV system. By a distributed coordination control approach, the conflicts and deadlocks between AGVs are solved online. The simulation results show the effectiveness and feasibility of this method.

Published
2017

12. Multi-AGV path planning with double-path constraints by using an improved genetic algorithm

Author

Feng Liu, Dongqing Wang, Han Zengliang, and Zhao Zhiyong

Subjects
0209 industrial biotechnology, Heredity, Computer science, Crossover, lcsh:Medicine, 02 engineering and technology, Any-angle path planning, 020901 industrial engineering & automation, Software, 0202 electrical engineering, electronic engineering, information engineering, Natural Selection, lcsh:Science, Multidisciplinary, Heuristic, Chromosome Biology, Population size, Applied Mathematics, Simulation and Modeling, Physical Sciences, 020201 artificial intelligence & image processing, Algorithms, Research Article, Optimization, Mathematical optimization, Evolutionary Processes, Population Size, Automated guided vehicle, Research and Analysis Methods, Chromosomes, Chromosomal Inheritance, Population Metrics, Genetic algorithm, Genetics, Computer Simulation, Motion planning, Molecular Biology Techniques, Molecular Biology, Evolutionary Biology, Population Biology, business.industry, Genetic Algorithms, lcsh:R, Gene Mapping, Biology and Life Sciences, Computational Biology, Reproducibility of Results, Cell Biology, Models, Theoretical, Path (graph theory), lcsh:Q, business, Mathematics
Abstract

This paper investigates an improved genetic algorithm on multiple automated guided vehicle (multi-AGV) path planning. The innovations embody in two aspects. First, three-exchange crossover heuristic operators are used to produce more optimal offsprings for getting more information than with the traditional two-exchange crossover heuristic operators in the improved genetic algorithm. Second, double-path constraints of both minimizing the total path distance of all AGVs and minimizing single path distances of each AGV are exerted, gaining the optimal shortest total path distance. The simulation results show that the total path distance of all AGVs and the longest single AGV path distance are shortened by using the improved genetic algorithm.

Published
2017

Catalog

Books, media, physical & digital resources
See catalog results