Multi-objective optimization path planning with moving target

Path planning or finding a collision-free path for mobile robots between starting position and its destination is a critical problem in robotics. This study is concerned with the multi objective optimization path planning problem of autonomous mobile robots with moving targets in dynamic environment...

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Bibliographic Details
Main Authors: Abed, B.M (Author), Jasim, W.M (Author)
Format: Article
Language:English
Published: Institute of Advanced Engineering and Science 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02105nam a2200217Ia 4500
001 10.11591-ijai.v11.i3.pp1184-1196
008 220718s2022 CNT 000 0 und d
020 |a 20894872 (ISSN) 
245 1 0 |a Multi-objective optimization path planning with moving target 
260 0 |b Institute of Advanced Engineering and Science  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.11591/ijai.v11.i3.pp1184-1196 
520 3 |a Path planning or finding a collision-free path for mobile robots between starting position and its destination is a critical problem in robotics. This study is concerned with the multi objective optimization path planning problem of autonomous mobile robots with moving targets in dynamic environment, with three objectives considered: path security, length and smoothness. Three modules are presented in the study. The first module is to combine particle swarm optimization algorithm (PSO) with bat algorithm (BA). The purpose of PSO is to optimize two important parameters of BA algorithm to minimize distance and smooth the path. The second module is to convert the generated infeasible points into feasible ones using a new local search algorithm (LS). The third module obstacle detection and avoidance (ODA) algorithm is proposed to complete the path, which is triggered when the mobile robot detects obstacles in its field of vision. ODA algorithm based on simulating human walking in a dark room. Several simulations with varying scenarios are run to test the validity of the proposed solution. The results show that the mobile robots are able to travel clearly and completely safe with short path, and smoothly proving the effectiveness of this method. © 2022, Institute of Advanced Engineering and Science. All rights reserved. 
650 0 4 |a Bat algorithm 
650 0 4 |a Dynamic environment 
650 0 4 |a Moving target 
650 0 4 |a Multi objective optimization 
650 0 4 |a Particle swarm optimization 
650 0 4 |a Path planning 
700 1 |a Abed, B.M.  |e author 
700 1 |a Jasim, W.M.  |e author 
773 |t IAES International Journal of Artificial Intelligence