No Cover Image

Journal article 977 views 336 downloads

Optimal Path Finding With Beetle Antennae Search Algorithm by Using Ant Colony Optimization Initialization and Different Searching Strategies

Xiangyuan Jiang, Zongyuan Lin, Tianhao He, Xiaojing Ma, Sile Ma, Shuai Li Orcid Logo

IEEE Access, Volume: 8, Pages: 15459 - 15471

Swansea University Author: Shuai Li Orcid Logo

  • jiang2020.pdf

    PDF | Version of Record

    Released under the terms of a Creative Commons Attribution 4.0 License (CC-BY).

    Download (14.05MB)

Check full text

DOI (Published version): 10.1109/access.2020.2965579

Abstract

Intelligent algorithm acts as one of the most important solutions to path planning problem. In order to solve the problems of poor real-time and low accuracy of the heuristic optimization algorithm in 3D path planning, this paper proposes a novel heuristic intelligent algorithm derived from the Beet...

Full description

Published in: IEEE Access
ISSN: 2169-3536
Published: Institute of Electrical and Electronics Engineers (IEEE) 2020
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa53741
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Intelligent algorithm acts as one of the most important solutions to path planning problem. In order to solve the problems of poor real-time and low accuracy of the heuristic optimization algorithm in 3D path planning, this paper proposes a novel heuristic intelligent algorithm derived from the Beetle Antennae Search (BAS) algorithm. The algorithm proposed in this paper has the advantages of wide search range and high search accuracy, and can still maintain a low time complexity when multiple mechanisms are introduced. This paper combines the BAS algorithm with three non-trivial mechanisms proposed to solve the problems of low search efficiency and poor convergence accuracy in 3D path planning. The algorithm contains three non-trivial mechanisms, including local fast search, aco initial path generation, and searching information orientation. At first, local fast search mechanism presents a specific bounded area and add fast iterative exploration to speed up the convergence of path finding. Then aco initial path generation mechanism is initialized by Ant Colony Optimization (ACO) as a pruning basis. The initialization of the ACO algorithm can quickly obtain an effective path. Using the exploration trend of this path, the algorithm can quickly obtain a locally optimal path. Thirdly, searching information orientation mechanism is employed for BAS algorithm to guarantee the stability of the path finding, thereby avoiding blind exploration and reducing wasted computing resources. Simulation results show that the algorithm proposed in this paper has higher search accuracy and exploration speed than other intelligent algorithms, and improves the adaptability of the path planning algorithms in different environments. The effectiveness of the proposed algorithm is verified in simulation.
Keywords: Beetle antennae search, optimal path finding, bio-inspired optimization, search orientation
College: Faculty of Science and Engineering
Start Page: 15459
End Page: 15471

Similar Items