Experimental study of path planning problem using EMCOA for a holonomic mobile robot

doi:10.23919/JSEE.2021.000123

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (6): 1450-1462.doi: 10.23919/JSEE.2021.000123

• SYSTEMS ENGINEERING • Previous Articles Next Articles

Experimental study of path planning problem using EMCOA for a holonomic mobile robot

Alireza MOHSENI*(), Vincent DUCHAINE(), Tony WONG

¹ Department of System Engineering, école de Technologie Supérieure, Montreal QC H3C 1K3, Canada

Received:2020-11-10 Accepted:2021-11-09 Online:2022-01-05 Published:2022-01-05
Contact: Alireza MOHSENI E-mail:ar.mohseni@yahoo.com;vincent.duchaine@etsmtl.ca
About author:|MOHSENI Alireza received his B.E. degree in electrical engineering from the Islamic Azad University (IAU), Tehran, Iran, in 2003, and his M.S. degree in mechatronics engineering from the IAU, Science and Research Branch, Tehran, in 2007. He was a researcher with the Multimedia University Cyberjaya, Malaysia, from 2008 to 2010. He is currently working toward his Ph.D. degree in automated manufacturing engineering focusing on robotics at école de Technologie Supérieure, Montreal, Canada. His research interests are industrial control systems, machine learning, computational intelligence, and robotic motion planning. E-mail: ar.mohseni@yahoo.com||DUCHAINE Vincent received his B.E. and Ph.D. degrees in mechanical engineering from Université Laval, Quebec, Canada, in 2005 and 2010, respectively. He joined the Biomimetics Dexterous Manipulation Laboratory, Stanford University, Stanford, USA, as a post-doctoral fellow. He is one of the cofounders of Robotiq, Inc., a Canadian company that designs and manufactures flexible robotic grippers. He is currently a professor with the Department of Automated Manufacturing Engineering, école de Technologie Supérieure, Montreal, Canada. His current research interests include control and sensor design for improving intuitiveness and safety of physical human-robot interaction. E-mail: vincent.duchaine@etsmtl.ca||WONG Tony holds his B.E. and M.E. degrees from école de Technologie supérieure in electrical engineering. He received his Ph.D. degree in computer engineering from école Polytechnique de Montréal. He joined the Systems Engineering Department of école de Technologie Supérieure in 1999. His research interests are multi-objective chance-constrained evolutionary algorithms, machine learning methods, and their application to service and manufacturing problems. E-mail: tony.wong@etsmtl.ca

Abstract

Abstract:

In this paper, a comparative study of the path planning problem using evolutionary algorithms, in comparison with classical methods such as the $ {{\rm{A}}}^{\mathbf{*}} $ algorithm, is presented for a holonomic mobile robot. The configured navigation system, which consists of the integration of sensors sources, map formatting, global and local path planners, and the base controller, aims to enable the robot to follow the shortest smooth path delicately. Grid-based mapping is used for scoring paths efficiently, allowing the determination of collision-free trajectories from the initial to the target position. This work considers the evolutionary algorithms, the mutated cuckoo optimization algorithm (MCOA) and the genetic algorithm (GA), as a global planner to find the shortest safe path among others. A non-uniform motion coefficient is introduced for MCOA in order to increase the performance of this algorithm. A series of experiments are accomplished and analyzed to confirm the performance of the global planner implemented on a holonomic mobile robot. The results of the experiments show the capacity of the planner framework with respect to the path planning problem under various obstacle layouts.

Key words: holonomic robot, path planning, evolutionary algorithm (EA)

Alireza MOHSENI, Vincent DUCHAINE, Tony WONG. Experimental study of path planning problem using EMCOA for a holonomic mobile robot[J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1450-1462.

Figures/Tables 13

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References 29

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Parameter		Value
Motor	Nominal voltage/V	24
	Nominal current/A	2.32
	Nominal torque/mN·m	82.7
	Moment of inertia/kg·mm²	13.5
	Rated speed/rpm	5250
Gearbox	Reduction ratio	26
Gearbox	Moment of inertia/kg·mm²	0.14
Encoder	Counts per revolution	4000

Parameter	Value
${N}_{{\rm{pop}}}$	14
$ {v}_{l} /m $	0
${n}_{ { {\rm{eggs} } }_{{\rm{max}}} }$	6
${v}_{h}/m$	5
${n}_{ { {\rm{eggs} } }_{{\rm{min}}} }$	3
a	5
b	1
$ \sigma $	0.09

Algorithm	Traversed time/s	Path length/m
EMCOA	21.46	6.68
GA	32.67	10.48
$ {\mathrm{A}}^{*} $	24.81	8.13

Algorithm	Traversed time/s	Path length/m
EMCOA	23.46	7.31
GA	>> 45	N/A
$ {\mathrm{A}}^{*} $	30.82	8.39

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Experimental study of path planning problem using EMCOA for a holonomic mobile robot

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