Interactive Learning Environment for Bio-Inspired Optimization Algorithms for UAV Path Planning

被引:42
作者
Duan, Haibin [1 ]
Li, Pei [2 ]
Shi, Yuhui [3 ]
Zhang, Xiangyin [2 ]
Sun, Changhao [2 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Automat Sci & Elect Engn, Sci & Technol Aircraft Control Lab, Beijing 100191, Peoples R China
[3] Xian Jiaotong Liverpool Univ, Dept Elect & Elect Engn, Suzhou 215123, Peoples R China
基金
中国国家自然科学基金;
关键词
Ant colony optimization; artificial bee colony; bio-inspired optimization; particle swarm optimization; path planning; unmanned aerial vehicles (UAVs); PARTICLE SWARM; COLONY; CONVERGENCE;
D O I
10.1109/TE.2015.2402196
中图分类号
G40 [教育学];
学科分类号
040101 [教育学原理];
摘要
This paper describes the development of BOLE, a MATLAB-based interactive learning environment, that facilitates the process of learning bio-inspired optimization algorithms, and that is dedicated exclusively to unmanned aerial vehicle path planning. As a complement to conventional teaching methods, BOLE is designed to help students consolidate the concepts taught in the course and motivate them to explore relevant issues of bio-inspired optimization algorithms through interactive and collaborative learning processes. BOLE differs from other similar tools in that it places greater emphasis on fundamental concepts than on complex mathematical equations. The learning tasks using BOLE can be classified into four steps: introduction, recognition, practice, and collaboration, according to task complexity. It complements traditional classroom teaching, enhancing learning efficiency and facilitating the assessment of student achievement, as verified by its practical application in an undergraduate course "Bio-Inspired Computing." Both objective and subjective measures were evaluated to assess the learning effectiveness.
引用
收藏
页码:276 / 281
页数:6
相关论文
共 23 条
[1]
JGOMAS: New Approach to AI Teaching [J].
Barella, Antonio ;
Valero, Soledad ;
Carrascosa, Carlos .
IEEE TRANSACTIONS ON EDUCATION, 2009, 52 (02) :228-235
[2]
Bhattacharya P, 2007, ISVD 2007: THE 4TH INTERNATIONAL SYMPOSIUM ON VORONOI DIAGRAMS IN SCIENCE AND ENGINEERING 2007, PROCEEDINGS, P38
[3]
Inspiration for optimization from social insect behaviour [J].
Bonabeau, E ;
Dorigo, M ;
Theraulaz, G .
NATURE, 2000, 406 (6791) :39-42
[4]
Educational Tool for Optimal Controller Tuning Using Evolutionary Strategies [J].
Carmona Morales, Daniel ;
Jimenez-Hornero, Jorge E. ;
Vazquez, Francisco ;
Morilla, Fernando .
IEEE TRANSACTIONS ON EDUCATION, 2012, 55 (01) :48-57
[5]
The particle swarm - Explosion, stability, and convergence in a multidimensional complex space [J].
Clerc, M ;
Kennedy, J .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2002, 6 (01) :58-73
[6]
Ant algorithms for discrete optimization [J].
Dorigo, M ;
Di Caro, G ;
Gambardella, LM .
ARTIFICIAL LIFE, 1999, 5 (02) :137-172
[7]
Ant system: Optimization by a colony of cooperating agents [J].
Dorigo, M ;
Maniezzo, V ;
Colorni, A .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 1996, 26 (01) :29-41
[8]
Development of a web-based control laboratory for automation technicians:: The three-tank system [J].
Dormido, R. ;
Vargas, H. ;
Duro, N. ;
Sanchez, J. ;
Dormido-Canto, S. ;
Farias, G. ;
Esquembre, F. ;
Dormido, S. .
IEEE TRANSACTIONS ON EDUCATION, 2008, 51 (01) :35-44
[9]
Duan H., 2014, Bio-inspired Computation in Unmanned Aerial Vehicles, DOI DOI 10.1007/978-3-642-41196-0_7
[10]
New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle [J].
Duan HaiBin ;
Shao Shan ;
Su BingWei ;
Zhang Lei .
SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2010, 53 (08) :2025-2031