Intelligent Beetle Antennae Search for UAV Sensing and Avoidance of Obstacles release_veret6anrretxasr42hg4bxb7y

by Qing Wu, Xudong Shen, Yuanzhe Jin, Zeyu Chen, Shuai Li, Ameer Hamza Khan, Dechao Chen

Published in Sensors by MDPI AG.

2019   Volume 19, p1758

Abstract

Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.
In application/xml+jats format

Archived Files and Locations

application/pdf  10.8 MB
file_6ojy7s5u75bjpmx2b63xl4rmoq
ira.lib.polyu.edu.hk (web)
web.archive.org (webarchive)
application/pdf  10.9 MB
file_unlqllvytrewfdnwesznxtahfm
web.archive.org (webarchive)
res.mdpi.com (web)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2019-04-12
Language   en ?
Container Metadata
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:  1424-8220
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 276f8dce-0ff8-4b7f-824c-0b4dbd779981
API URL: JSON