eprintid: 4741
rev_number: 11
eprint_status: archive
userid: 285
dir: disk0/00/00/47/41
datestamp: 2022-08-22 03:57:18
lastmod: 2022-08-22 03:57:18
status_changed: 2022-08-22 03:57:18
type: conference_item
metadata_visibility: show
creators_name: Hoang, Van Truong
creators_name: Phung, Manh Duong
creators_id: duongpm@vnu.edu.vn
title: Enhanced Teaching-Learning-based Optimization for 3D Path Planning of Multicopter UAVs
ispublished: pub
subjects: Aerospace
subjects: ECE
subjects: IT
subjects: isi_scopus_conf
divisions: fac_fet
abstract: This paper introduces a new path planning algorithm for unmanned aerial vehicles (UAVs) based on the teaching-learning-based optimization (TLBO) technique. We first define an objective function that incorporates requirements on the path length and constraints on the movement and safe operation of UAVs to convert the path planning into an optimization problem. The optimization algorithm named Multi-subject TLBO is then proposed to minimize the formulated objective function. The algorithm is developed based on TLBO but enhanced with new operations including mutation, elite selection and multi-subject training to improve the solution quality and speed up the convergence rate. Comparison with state-of-the-art algorithms and experiments with real UAVs have been conducted to evaluate the performance of the proposed algorithm. The results confirm its validity and effectiveness in generating optimal, collision-free and flyable paths for UAVs in complex operating environments.
date: 2022-04-02
date_type: published
official_url: https://link.springer.com/chapter/10.1007/978-3-030-99666-6_107
full_text_status: public
pres_type: paper
pagerange: 743-753
event_title: The International Conference on Advanced Mechanical Engineering, Automation, and Sustainable Development 2021 (AMAS2021)
event_type: conference
refereed: TRUE
citation:   Hoang, Van Truong and Phung, Manh Duong  (2022) Enhanced Teaching-Learning-based Optimization for 3D Path Planning of Multicopter UAVs.  In: The International Conference on Advanced Mechanical Engineering, Automation, and Sustainable Development 2021 (AMAS2021).     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4741/1/edited_Hoang-Phung2022_Chapter_EnhancedTeaching-Learning-Base.pdf