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Path Planning for Unmanned Aerial Vehicle Using a Mix-Strategy-Based Gravitational Search Algorithm
- Source :
- IEEE Access, Vol 9, Pp 57033-57045 (2021)
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- Path planning is a global optimization problem aims to program the optimal flight path for Unmanned Aerial Vehicle (UAV) that has short length and suffers from low threat. In this paper, we present a Mixed-Strategy based Gravitational Search Algorithm (MSGSA) for the path planning. In MSGSA, an adaptive adjustment strategy for the gravitational constant attenuation factor alpha ( $\alpha$ ) is presented firstly, in which the value of $\alpha $ is adjusted based on the evolutionary state of the particles. This helps to adaptively balance the exploration and exploitation of the algorithm. In addition, to further alleviate the premature convergence problem, a Cauchy mutation strategy is developed for MSGSA. In this strategy, only when the global best particle cannot be further improved for several times the mutation is executed. In the MSGSA based path planning procedure, we construct an objective function using the flight length cost, threat area cost, and turning angle constraint to decrease the flight risk and obtain the smoother path. For performance evaluation, the MSGSA is applied to two typical simulated flight missions with complex flight environments, including user-defined forbidden flying areas, Radar, missile, artillery and anti-aircraft gun. The obtained flight paths are compared with that of the standard Gravitational Search Algorithm (GSA) and two improved variants of GSA, i.e. gbest -guided GSA (GGSA), and hybrid Particle Swarm Optimization and GSA (PSOGSA). The experimental results demonstrate the superiority of the MSGSA based method in terms of the solution quality, robustness, as well as the constraint-handling ability.
- Subjects :
- 0209 industrial biotechnology
General Computer Science
Linear programming
Computer science
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
020901 industrial engineering & automation
Missile
unmanned aerial vehicle (UAV)
Control theory
Robustness (computer science)
adaptive alpha-adjusting
Convergence (routing)
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
Motion planning
Path planning
Cauchy mutation
General Engineering
Particle swarm optimization
gravitational search algorithm (GSA)
TK1-9971
Path (graph theory)
020201 artificial intelligence & image processing
Electrical engineering. Electronics. Nuclear engineering
Premature convergence
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....9a1bdba06026a2d30a686bbf14dcb320