A parallel compact cuckoo search algorithm for three-dimensional path planning

Pei-Cheng Song; Jeng-Shyang Pan; Shu-Chuan Chu

doi:10.1016/j.asoc.2020.106443

A parallel compact cuckoo search algorithm for three-dimensional path planning

Pei-Cheng Song, Jeng-Shyang Pan, Shu-Chuan Chu

College of Science and Engineering

Research output: Contribution to journal › Article › peer-review

105 Citations (Scopus)

Abstract

The three-dimensional (3D) path planning of unmanned robots focuses on avoiding collisions with obstacles and finding an optimized path to the target location in a complex three-dimensional environment. An improved cuckoo search algorithm based on compact and parallel techniques for three-dimensional path planning problems is proposed. This paper implements the compact cuckoo search algorithm, and then, a new parallel communication strategy is proposed. The compact scheme can effectively save the memory of the unmanned robot. The parallel scheme can increase the accuracy and achieve faster convergence. The proposed algorithm is tested on several selected functions and three-dimensional path planning. Results compared with other methods show that the proposed algorithm can provide more competitive results and achieve more efficient execution.

Original language	English
Article number	106443
Number of pages	16
Journal	Applied Soft Computing
Volume	94
DOIs	https://doi.org/10.1016/j.asoc.2020.106443
Publication status	Published - Sept 2020

Keywords

3D path planning
Compact strategy
Cuckoo search algorithm
Parallel communication strategy

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abstract = "The three-dimensional (3D) path planning of unmanned robots focuses on avoiding collisions with obstacles and finding an optimized path to the target location in a complex three-dimensional environment. An improved cuckoo search algorithm based on compact and parallel techniques for three-dimensional path planning problems is proposed. This paper implements the compact cuckoo search algorithm, and then, a new parallel communication strategy is proposed. The compact scheme can effectively save the memory of the unmanned robot. The parallel scheme can increase the accuracy and achieve faster convergence. The proposed algorithm is tested on several selected functions and three-dimensional path planning. Results compared with other methods show that the proposed algorithm can provide more competitive results and achieve more efficient execution.",

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AB - The three-dimensional (3D) path planning of unmanned robots focuses on avoiding collisions with obstacles and finding an optimized path to the target location in a complex three-dimensional environment. An improved cuckoo search algorithm based on compact and parallel techniques for three-dimensional path planning problems is proposed. This paper implements the compact cuckoo search algorithm, and then, a new parallel communication strategy is proposed. The compact scheme can effectively save the memory of the unmanned robot. The parallel scheme can increase the accuracy and achieve faster convergence. The proposed algorithm is tested on several selected functions and three-dimensional path planning. Results compared with other methods show that the proposed algorithm can provide more competitive results and achieve more efficient execution.

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KW - Compact strategy

KW - Cuckoo search algorithm

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JO - Applied Soft Computing

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A parallel compact cuckoo search algorithm for three-dimensional path planning

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Keywords

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