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Three-Dimensional Path Planning for Uninhabited Combat Aerial Vehicle Based on Predator-Prey Pigeon-Inspired Optimization in Dynamic Environment
- Source :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics. 14:97-107
- Publication Year :
- 2017
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2017.
-
Abstract
- Three-dimension path planning of uninhabited combat aerial vehicle (UCAV) is a complicated optimal problem, which mainly focused on optimizing the flight route considering the different types of constrains under complex combating environment. A novel predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the UCAV three-dimension path planning problem in dynamic environment. Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. In this algorithm, map and compass operator model and landmark operator model are used to search the best result of a function. The prey-predator concept is adopted to improve global best properties and enhance the convergence speed. The characteristics of the optimal path are presented in the form of a cost function. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO, particle swarm optimization (PSO), and different evolution (DE) in solving UCAV three-dimensional path planning problems.
- Subjects :
- 0209 industrial biotechnology
Mathematical optimization
Aircraft
02 engineering and technology
Models, Biological
020901 industrial engineering & automation
Artificial Intelligence
Compass
Convergence (routing)
0202 electrical engineering, electronic engineering, information engineering
Genetics
Animals
Computer Simulation
Motion planning
Landmark
Raptors
business.industry
Applied Mathematics
Particle swarm optimization
Function (mathematics)
Flight, Animal
Predatory Behavior
Path (graph theory)
020201 artificial intelligence & image processing
Artificial intelligence
Operator model
business
Algorithms
Spatial Navigation
Biotechnology
Subjects
Details
- ISSN :
- 23740043 and 15455963
- Volume :
- 14
- Database :
- OpenAIRE
- Journal :
- IEEE/ACM Transactions on Computational Biology and Bioinformatics
- Accession number :
- edsair.doi.dedup.....c7840eecafa4a194a388a656d8e71ed1