Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm
Joint Authors
Liu, Weirong
Lian, Jianfang
Yu, Wentao
Xiao, Kui
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-02-20
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
This paper proposed a cubic spline interpolation-based path planning method to maintain the smoothness of moving the robot’s path.
Several path nodes were selected as control points for cubic spline interpolation.
A full path was formed by interpolating on the path of the starting point, control points, and target point.
In this paper, a novel chaotic adaptive particle swarm optimization (CAPSO) algorithm has been proposed to optimize the control points in cubic spline interpolation.
In order to improve the global search ability of the algorithm, the position updating equation of the particle swarm optimization (PSO) is modified by the beetle foraging strategy.
Then, the trigonometric function is adopted for the adaptive adjustment of the control parameters for CAPSO to weigh global and local search capabilities.
At the beginning of the algorithm, particles can explore better regions in the global scope with a larger speed step to improve the searchability of the algorithm.
At the later stage of the search, particles do fine search around the extremum points to accelerate the convergence speed of the algorithm.
The chaotic map is also used to replace the random parameter of the PSO to improve the diversity of particle swarm and maintain the original random characteristics.
Since all chaotic maps are different, the performance of six benchmark functions was tested to choose the most suitable one.
The CAPSO algorithm was tested for different number of control points and various obstacles.
The simulation results verified the effectiveness of the proposed algorithm compared with other algorithms.
And experiments proved the feasibility of the proposed model in different dynamic environments.
American Psychological Association (APA)
Lian, Jianfang& Yu, Wentao& Xiao, Kui& Liu, Weirong. 2020. Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1193587
Modern Language Association (MLA)
Lian, Jianfang…[et al.]. Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering No. 2020 (2020), pp.1-20.
https://search.emarefa.net/detail/BIM-1193587
American Medical Association (AMA)
Lian, Jianfang& Yu, Wentao& Xiao, Kui& Liu, Weirong. Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-20.
https://search.emarefa.net/detail/BIM-1193587
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1193587