A review: On path planning strategies for navigation of mobile robot

This paper presents the rigorous study of mobile robot navigation techniques used so far. The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap. The...

Full description

Bibliographic Details
Main Authors: B.K. Patle, Ganesh Babu L, Anish Pandey, D.R.K. Parhi, A. Jagadeesh
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2019-08-01
Series:Defence Technology
Online Access:http://www.sciencedirect.com/science/article/pii/S2214914718305130
id doaj-95c6013a282e4adfbbfde0354d4a2421
record_format Article
spelling doaj-95c6013a282e4adfbbfde0354d4a24212021-05-02T03:48:54ZengKeAi Communications Co., Ltd.Defence Technology2214-91472019-08-01154582606A review: On path planning strategies for navigation of mobile robotB.K. Patle0Ganesh Babu L1Anish Pandey2D.R.K. Parhi3A. Jagadeesh4Department of Mechanical Engineering, CVR College of Engineering, Hyderabad, India; Corresponding author.Department of Mechatronics Engineering, Tishik International University, Erbil, IraqDepartment of Mechanical Engineering, KITS University Bhubaneshwar, IndiaDepartment of Mechanical Engineering, NIT Rourkela, IndiaDepartment of Mechanical Engineering, KL University, Guntur, IndiaThis paper presents the rigorous study of mobile robot navigation techniques used so far. The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap. The classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (APF); reactive approaches such as genetic algorithm (GA), fuzzy logic (FL), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization (BFO), artificial bee colony (ABC), cuckoo search (CS), shuffled frog leaping algorithm (SFLA) and other miscellaneous algorithms (OMA) are considered for study. The navigation over static and dynamic condition is analyzed (for single and multiple robot systems) and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches. It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm. Hence, reactive approaches are more popular and widely used for path planning of mobile robot. The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics. Keywords: Mobile robot navigation, Path planning, Classical approaches, Reactive approaches, Artificial intelligencehttp://www.sciencedirect.com/science/article/pii/S2214914718305130
collection DOAJ
language English
format Article
sources DOAJ
author B.K. Patle
Ganesh Babu L
Anish Pandey
D.R.K. Parhi
A. Jagadeesh
spellingShingle B.K. Patle
Ganesh Babu L
Anish Pandey
D.R.K. Parhi
A. Jagadeesh
A review: On path planning strategies for navigation of mobile robot
Defence Technology
author_facet B.K. Patle
Ganesh Babu L
Anish Pandey
D.R.K. Parhi
A. Jagadeesh
author_sort B.K. Patle
title A review: On path planning strategies for navigation of mobile robot
title_short A review: On path planning strategies for navigation of mobile robot
title_full A review: On path planning strategies for navigation of mobile robot
title_fullStr A review: On path planning strategies for navigation of mobile robot
title_full_unstemmed A review: On path planning strategies for navigation of mobile robot
title_sort review: on path planning strategies for navigation of mobile robot
publisher KeAi Communications Co., Ltd.
series Defence Technology
issn 2214-9147
publishDate 2019-08-01
description This paper presents the rigorous study of mobile robot navigation techniques used so far. The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap. The classical approaches such as cell decomposition (CD), roadmap approach (RA), artificial potential field (APF); reactive approaches such as genetic algorithm (GA), fuzzy logic (FL), neural network (NN), firefly algorithm (FA), particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization (BFO), artificial bee colony (ABC), cuckoo search (CS), shuffled frog leaping algorithm (SFLA) and other miscellaneous algorithms (OMA) are considered for study. The navigation over static and dynamic condition is analyzed (for single and multiple robot systems) and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches. It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm. Hence, reactive approaches are more popular and widely used for path planning of mobile robot. The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics. Keywords: Mobile robot navigation, Path planning, Classical approaches, Reactive approaches, Artificial intelligence
url http://www.sciencedirect.com/science/article/pii/S2214914718305130
work_keys_str_mv AT bkpatle areviewonpathplanningstrategiesfornavigationofmobilerobot
AT ganeshbabul areviewonpathplanningstrategiesfornavigationofmobilerobot
AT anishpandey areviewonpathplanningstrategiesfornavigationofmobilerobot
AT drkparhi areviewonpathplanningstrategiesfornavigationofmobilerobot
AT ajagadeesh areviewonpathplanningstrategiesfornavigationofmobilerobot
AT bkpatle reviewonpathplanningstrategiesfornavigationofmobilerobot
AT ganeshbabul reviewonpathplanningstrategiesfornavigationofmobilerobot
AT anishpandey reviewonpathplanningstrategiesfornavigationofmobilerobot
AT drkparhi reviewonpathplanningstrategiesfornavigationofmobilerobot
AT ajagadeesh reviewonpathplanningstrategiesfornavigationofmobilerobot
_version_ 1721495532976734208