Development of Robot Navigation System with Collision Free Path Planning Algorithm

Htun Myint

doi:doi:10.11648/j.mlr.20180303.12

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Development of Robot Navigation System with Collision Free Path Planning Algorithm

Htun Myint

Published in Machine Learning Research (Volume 3, Issue 3)

Received: 3 August 2018 Accepted: 6 September 2018 Published: 12 October 2018

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Abstract

Mobile robots have been successfully used in many fields due to their abilities to perform difficult tasks in hazardous environments, such as robot rescuing, space exploring and their various promising applications in the daily lives. Robot path planning is a key issue in robot navigation which is a kernel part in mobile robot technology. Robot path planning is to generate a collision-free path in an environment while satisfying some optimization criteria. Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this research work, an evolutionary algorithm to solve the robot path planning problem is devised. A method of robot path planning in partially unknown environments based on A star (A*) algorithm was proposed. The proposed algorithm allows a mobile robot to navigate through static obstacles and finds its path in order to reach from its initial position to the target without collision. In addition, the environment is partially unknown for the robot due to the limit detection range of its sensors. The robot processor updates its information during the motion. The simulations are performed in different static environments, and the results show that the robot reaches its target with colliding free obstacles. The optimal path is generated with this method when the robot reaches its target. The simulation results are developed by MATLAB environments.

Published in	Machine Learning Research (Volume 3, Issue 3)
DOI	10.11648/j.mlr.20180303.12
Page(s)	60-68
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Collision Free Path, Robot Navigation, MATLAB, A Star, Path Planning Algorithm

References

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[7]	R. Holte, T. Mkadmi, R. Zimmer, and A. MacDonald. “Speeding Up Problem-Solving by Abstraction: A Graph Oriented Approach”. Artificial Intelligence Journal, 85(1-2), pp. 321-361, 1996.
[8]	Samuel Grant Dawson Williams, “Using the A-Star Path-Finding Algorithm for Solving General and Constrained Inverse Kinematics Problems”, Japan, 2008.
[9]	Mohd Azlan Shah Abd Rahim and Illani Mohd Nawi, “Path Planning Automated Guided Robot”, Proceedings of the World Congress on Engineering and Computer Science 2008 WCECS 2008, October 22 - 24, 2008, San Francisco, USA, 2008.
[10]	Bruno Siciliano, Lorenzo Sciavicco, Luigi Villani, and Giuseppe Oriolo, “Robotics Modelling, Planning and Control”, Spain, 2009.
[11]	Giacomo Nannicini, “Point-to-Point Shortest Paths on Dynamic Time-Dependent Road Networks”, French, 2009.
[12]	Rehman Tariq Butt, “Performance Comparison of AI Algorithms Anytime Algorithms”, Sweden, 2008.
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[14]	Subramanian MB, Sudhagar K, Rajarajeswari G. Design of navigation control architecture for an autonomous mobile robot agent. Indian Journal of Science and Technology. 2016 Mar; 9(10). Doi no: 10.17485/ijst/2016/v9i10/85769.
[15]	Prasad KM, Reddy ARM, Rao KV. Anomaly based Real Time Prevention of under rated App-DDOS attacks on web: An experiential metrics based machine learning approach. Indian Journal of Science and Technology. 2016 Jul; 9(27). Doi no: 10.17485/ijst/2016/v9i27/87872.
[16]	Murikipudi A, Prakash V, Vigneswaran T. Performance analysis of real time operating system with general purpose operating system for mobile robotic system. Indian Journal of Science and Technology. 2015 Aug; 8(18). Doi no:10.17485/ijst/2015/v8i19/77017.
[17]	Suresh KS, Vaithiyanathan V, Venugopal S. Layered approach for three dimensional collision free robot path planning using genetic algorithm. Indian Journal of Science and Technology. 2015 Dec; 8(35). Doi no:10.17485/ijst/2015/v8i35/86639.

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APA Style

Htun Myint. (2018). Development of Robot Navigation System with Collision Free Path Planning Algorithm. Machine Learning Research, 3(3), 60-68. https://doi.org/10.11648/j.mlr.20180303.12

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ACS Style

Htun Myint. Development of Robot Navigation System with Collision Free Path Planning Algorithm. Mach. Learn. Res. 2018, 3(3), 60-68. doi: 10.11648/j.mlr.20180303.12

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AMA Style

Htun Myint. Development of Robot Navigation System with Collision Free Path Planning Algorithm. Mach Learn Res. 2018;3(3):60-68. doi: 10.11648/j.mlr.20180303.12

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@article{10.11648/j.mlr.20180303.12,
  author = {Htun Myint},
  title = {Development of Robot Navigation System with Collision Free Path Planning Algorithm},
  journal = {Machine Learning Research},
  volume = {3},
  number = {3},
  pages = {60-68},
  doi = {10.11648/j.mlr.20180303.12},
  url = {https://doi.org/10.11648/j.mlr.20180303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20180303.12},
  abstract = {Mobile robots have been successfully used in many fields due to their abilities to perform difficult tasks in hazardous environments, such as robot rescuing, space exploring and their various promising applications in the daily lives. Robot path planning is a key issue in robot navigation which is a kernel part in mobile robot technology. Robot path planning is to generate a collision-free path in an environment while satisfying some optimization criteria. Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this research work, an evolutionary algorithm to solve the robot path planning problem is devised. A method of robot path planning in partially unknown environments based on A star (A*) algorithm was proposed. The proposed algorithm allows a mobile robot to navigate through static obstacles and finds its path in order to reach from its initial position to the target without collision. In addition, the environment is partially unknown for the robot due to the limit detection range of its sensors. The robot processor updates its information during the motion. The simulations are performed in different static environments, and the results show that the robot reaches its target with colliding free obstacles. The optimal path is generated with this method when the robot reaches its target. The simulation results are developed by MATLAB environments.},
 year = {2018}
}

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TY  - JOUR
T1  - Development of Robot Navigation System with Collision Free Path Planning Algorithm
AU  - Htun Myint
Y1  - 2018/10/12
PY  - 2018
N1  - https://doi.org/10.11648/j.mlr.20180303.12
DO  - 10.11648/j.mlr.20180303.12
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 60
EP  - 68
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20180303.12
AB  - Mobile robots have been successfully used in many fields due to their abilities to perform difficult tasks in hazardous environments, such as robot rescuing, space exploring and their various promising applications in the daily lives. Robot path planning is a key issue in robot navigation which is a kernel part in mobile robot technology. Robot path planning is to generate a collision-free path in an environment while satisfying some optimization criteria. Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this research work, an evolutionary algorithm to solve the robot path planning problem is devised. A method of robot path planning in partially unknown environments based on A star (A*) algorithm was proposed. The proposed algorithm allows a mobile robot to navigate through static obstacles and finds its path in order to reach from its initial position to the target without collision. In addition, the environment is partially unknown for the robot due to the limit detection range of its sensors. The robot processor updates its information during the motion. The simulations are performed in different static environments, and the results show that the robot reaches its target with colliding free obstacles. The optimal path is generated with this method when the robot reaches its target. The simulation results are developed by MATLAB environments.
VL  - 3
IS  - 3
ER  -

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Author Information

Htun Myint

Department of Electronic Engineering, Technological University (Panglong), Panglong, Myanmar

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Plain Text BibTeX RIS

APA Style

Htun Myint. (2018). Development of Robot Navigation System with Collision Free Path Planning Algorithm. Machine Learning Research, 3(3), 60-68. https://doi.org/10.11648/j.mlr.20180303.12

Copy | Download

ACS Style

Htun Myint. Development of Robot Navigation System with Collision Free Path Planning Algorithm. Mach. Learn. Res. 2018, 3(3), 60-68. doi: 10.11648/j.mlr.20180303.12

Copy | Download

AMA Style

Htun Myint. Development of Robot Navigation System with Collision Free Path Planning Algorithm. Mach Learn Res. 2018;3(3):60-68. doi: 10.11648/j.mlr.20180303.12

Copy | Download

@article{10.11648/j.mlr.20180303.12,
  author = {Htun Myint},
  title = {Development of Robot Navigation System with Collision Free Path Planning Algorithm},
  journal = {Machine Learning Research},
  volume = {3},
  number = {3},
  pages = {60-68},
  doi = {10.11648/j.mlr.20180303.12},
  url = {https://doi.org/10.11648/j.mlr.20180303.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20180303.12},
  abstract = {Mobile robots have been successfully used in many fields due to their abilities to perform difficult tasks in hazardous environments, such as robot rescuing, space exploring and their various promising applications in the daily lives. Robot path planning is a key issue in robot navigation which is a kernel part in mobile robot technology. Robot path planning is to generate a collision-free path in an environment while satisfying some optimization criteria. Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this research work, an evolutionary algorithm to solve the robot path planning problem is devised. A method of robot path planning in partially unknown environments based on A star (A*) algorithm was proposed. The proposed algorithm allows a mobile robot to navigate through static obstacles and finds its path in order to reach from its initial position to the target without collision. In addition, the environment is partially unknown for the robot due to the limit detection range of its sensors. The robot processor updates its information during the motion. The simulations are performed in different static environments, and the results show that the robot reaches its target with colliding free obstacles. The optimal path is generated with this method when the robot reaches its target. The simulation results are developed by MATLAB environments.},
 year = {2018}
}

Copy | Download

TY  - JOUR
T1  - Development of Robot Navigation System with Collision Free Path Planning Algorithm
AU  - Htun Myint
Y1  - 2018/10/12
PY  - 2018
N1  - https://doi.org/10.11648/j.mlr.20180303.12
DO  - 10.11648/j.mlr.20180303.12
T2  - Machine Learning Research
JF  - Machine Learning Research
JO  - Machine Learning Research
SP  - 60
EP  - 68
PB  - Science Publishing Group
SN  - 2637-5680
UR  - https://doi.org/10.11648/j.mlr.20180303.12
AB  - Mobile robots have been successfully used in many fields due to their abilities to perform difficult tasks in hazardous environments, such as robot rescuing, space exploring and their various promising applications in the daily lives. Robot path planning is a key issue in robot navigation which is a kernel part in mobile robot technology. Robot path planning is to generate a collision-free path in an environment while satisfying some optimization criteria. Mobile robot path planning is a nondeterministic polynomial time (NP) problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this research work, an evolutionary algorithm to solve the robot path planning problem is devised. A method of robot path planning in partially unknown environments based on A star (A*) algorithm was proposed. The proposed algorithm allows a mobile robot to navigate through static obstacles and finds its path in order to reach from its initial position to the target without collision. In addition, the environment is partially unknown for the robot due to the limit detection range of its sensors. The robot processor updates its information during the motion. The simulations are performed in different static environments, and the results show that the robot reaches its target with colliding free obstacles. The optimal path is generated with this method when the robot reaches its target. The simulation results are developed by MATLAB environments.
VL  - 3
IS  - 3
ER  -

Copy | Download