Intelligent Bézier curve-based path planning model using Chaotic Particle Swarm Optimization algorithm

Path planning algorithms have been used in different applications with the aim of finding a suitable collision-free path which satisfies some certain criteria such as the shortest path length and smoothness; thus, defining a suitable curve to describe path is essential. The main goal of these algori...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Cluster computing Ročník 22; číslo Suppl 2; s. 4745 - 4766
Hlavní autori: Tharwat, Alaa, Elhoseny, Mohamed, Hassanien, Aboul Ella, Gabel, Thomas, Kumar, Arun
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.03.2019
Springer Nature B.V
Predmet:
Algorithms
Collision avoidance
Computer Communication Networks
Computer Science
Curves
Genetic algorithms
Operating Systems
Optimization algorithms
Particle swarm optimization
Processor Architectures
Robots
Shortest-path problems
Smoothness
Unmanned aerial vehicles
Chaos
Path planning
Bézier curve
Particle Swarm Optimization (PSO)
ISSN:1386-7857, 1573-7543
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Path planning algorithms have been used in different applications with the aim of finding a suitable collision-free path which satisfies some certain criteria such as the shortest path length and smoothness; thus, defining a suitable curve to describe path is essential. The main goal of these algorithms is to find the shortest and smooth path between the starting and target points. This paper makes use of a Bézier curve-based model for path planning. The control points of the Bézier curve significantly influence the length and smoothness of the path. In this paper, a novel Chaotic Particle Swarm Optimization (CPSO) algorithm has been proposed to optimize the control points of Bézier curve, and the proposed algorithm comes in two variants: CPSO-I and CPSO-II. Using the chosen control points, the optimum smooth path that minimizes the total distance between the starting and ending points is selected. To evaluate the CPSO algorithm, the results of the CPSO-I and CPSO-II algorithms are compared with the standard PSO algorithm. The experimental results proved that the proposed algorithm is capable of finding the optimal path. Moreover, the CPSO algorithm was tested against different numbers of control points and obstacles, and the CPSO algorithm achieved competitive results.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1386-7857
1573-7543
DOI:10.1007/s10586-018-2360-3