Maze Solving Mobile Robot Based on Image Processing and Graph Theory
Abstract
:1. Introduction
2. MazeImage Processing
3. Path Planning
4. Experimental Verification
Algorithm 1 Instruction transformation algorithm pseudocode. 
Require: Path vector

5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
 Gross, J.L.; Yellen, J.; Anderson, M. Graph Theory and Its Applications, 3rd ed.; CRC Press: Boca Raton, FL, USA; Taylos & Francis Group: Boca Raton, FL, USA, 2019. [Google Scholar]
 Sadik, A.M.J.; Dhali, M.A.; Farid, H.M.A.B.; Rashid, T.U.; Syeed, A. A Comprehensive and Comparative Study of MazeSolving Techniques by Implementing Graph Theory. In Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence, Sanya, China, 23–24 October 2010; pp. 52–56. [Google Scholar]
 Kumar, N.; Kaur, S. A Review of Various Maze Solving Algorithms Based on Graph Theory. Int. J. Sci. Res. Dev. 2019, 6, 431–434. [Google Scholar]
 Niemczyk, R.; Zawiślak, S. Review of Maze Solving Algorithms for 2D Maze and Their Visualisation. In Engineer of the XXI Century. EngineerXXI 2018. Mechanisms and Machine Science; Zawiślak, S., Rysiński, J., Eds.; Springer: Cham, Switzerland, 2020; Volume 70. [Google Scholar]
 Alamri, S.; Alshehri, S.; Alshehri, W.; Alamri, H.; Alaklabi, A.; Alhmiedat, T. Autonomous Maze Solving Robotics: Algorithms and Systems. Int. J. Mech. Eng. Robot. Res. 2021, 10, 668–675. [Google Scholar] [CrossRef]
 Alamri, S.; Alamri, H.; Alshehri, W.; Alshehri, S.; Alaklabi, A.; Alhmiedat, T. An autonomous mazesolving robotic system based on an enhanced wallfollower approach. Machines 2023, 11, 249. [Google Scholar] [CrossRef]
 Liu, L.; Wang, X.; Yang, X.; Liu, H.; Li, J.; Wang, P. Path planning techniques for mobile robots: Review and prospect. Expert Syst. Appl. 2023, 227, 120254. [Google Scholar] [CrossRef]
 Zang, X.; Iqbal, S.; Zhu, Y.; Liu, X.; Zhao, J. Applications of chaotic dynamics in robotics. Int. J. Adv. Robot. Syst. 2016, 13. [Google Scholar] [CrossRef]
 Martyushev, N.V.; Malozyomov, B.V.; Sorokova, S.N.; Efremenkov, E.A.; Valuev, D.V.; Qi, M. Review Models and Methods for Determining and Predicting the Reliability of Technical Systems and Transport. Mathematics 2023, 11, 3317. [Google Scholar] [CrossRef]
 Liu, X.; Gong, D. A comparative study of Astar algorithms for search and rescue in perfect maze. In Proceedings of the International Conference on Electric Information and Control Engineering, Wuhan, China, 15–17 April 2011; pp. 24–27. [Google Scholar]
 Huh, D.J.; Park, J.H.; Huh, U.Y.; Kim, H.I. Path planning and navigation for autonomous mobile robot. In Proceedings of the 28th Annual Conference of the Industrial Electronics Society. IECON 02, Seville, Spain, 5–8 November 2002; Volume 2, pp. 1538–1542. [Google Scholar]
 Rahnama, B.; Ozdemir, M.; Kiran, Y.; Elci, A. Design and Implementation of a Novel Weighted Shortest Path Algorithm for Maze Solving Robots. In Proceedings of the 37th International Computer Software and Applications Conference Workshops (COMPSACW), Tokyo, Japan, 22–26 July 2013; pp. 328–332. [Google Scholar]
 Chang, K.C.; Zhou, Y.; Shoaib, A.M.; Chu, K.C.; Izhar, M.; Ullah, S.; Lin, Y.C. Shortest Distance Maze Solving Robot. In Proceedings of the 2020 IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS), Dalian, China, 20–22 March 2020; pp. 283–286. [Google Scholar]
 Covaci, R.; Harja, G.; Nascu, I. Autonomous Maze Solving Robot. In Proceedings of the 2020 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), ClujNapoca, Romania, 21–23 May 2020; pp. 1–4. [Google Scholar]
 Pame, Y.G.; Kottawar, V.G.; Mahajan, Y.V. A Novel Approach to Maze Solving Algorithm. In Proceedings of the 2023 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 1–3 March 2023; pp. 1–6. [Google Scholar]
 Rahnama, B.; Elçi, A.; Metani, S. An Image Processing Approach to Solve Labyrinth Discovery Robotics Problem. In Proceedings of the 36th Annual Computer Software and Applications Conference Workshops, Izmir, Turkey, 16–20 July 2012; pp. 631–636. [Google Scholar]
 Joshi, H.N.; Shinde, J.P. An Image Based Path Planning And Motion Planning for Autonomous Robot. Int. J. Comput. Sci. Inf. Technol. 2014, 5, 4844–4847. [Google Scholar]
 Aqel, M.O.A.; Issa, A.; Khdair, M.; ElHabbash, M.; AbuBaker, M.; Massoud, M. Intelligent Maze Solving Robot Based on Image Processing and Graph Theory Algorithms. In Proceedings of the 2017 International Conference on Promising Electronic Technologies (ICPET), Deir ElBalah, Palestine, 16–17 October 2017; pp. 48–53. [Google Scholar]
 Murata, Y.; Mitani, Y. A Fast and Shorter Path Finding Method for Maze Images by Image Processing Techniques and Graph Theory. J. Image Graph. 2014, 2, 89–93. [Google Scholar] [CrossRef]
 Kathe, O.; Turkar, V.; Jagtap, A.; Gidaye, G. Maze solving robot using image processing. In Proceedings of the Bombay Section Symposium (IBSS), Mumbai, India, 10–11 September 2015; pp. 1–5. [Google Scholar]
 Ambeskar, A.; Turkar, V.; Bondre, A.; Gosavi, H. Path finding robot using image processing. In Proceedings of the 2016 International Conference on Inventive Computation Technologies (ICICT), Coimbatore, India, 26–27 August 2016; pp. 1–6. [Google Scholar]
 Ambeskar, A.; Bondre, A.; Turkar, V.; Gosavi, H. Intuitive solution for Robot Maze Problem using Image Processing. In Proceedings of the Bombay Section Signature Conference (IBSSC), Mumbai, India, 26–28 July 2019; pp. 1–6. [Google Scholar]
 Althöfer, K.; Fraser, D.A.; Bugmann, G. Rapid path planning for robotic manipulators using an emulated resistive grid. Electron. Lett. 1995, 31, 1960–1961. [Google Scholar] [CrossRef]
 HernándezMejía, C.; VázquezLeal, H.; SánchezGonzález, A.; CoronaAvelizapa, A. A Novel and Reduced CPU Time Modeling and Simulation Methodology for Path Planning Based on Resistive Grids. Arab. J. Sci. Eng. 2019, 44, 2321–2333. [Google Scholar] [CrossRef]
 HernándezMejía, C.; TorresMuñoz, D.; InzunzaGonzález, E.; SánchezLópez, C. Exploring Robotical Implementation for Planning of Collisionfree Logistical Paths Using RGPPM Algorithm. Iran. J. Sci. Technol. Trans. Electr. Eng. 2023, 47, 221–231. [Google Scholar] [CrossRef]
 Pershin, Y.V.; Di Ventra, M. Solving mazes with memristors: A massively parallel approach. Phys. Rev. E 2011, 84, 046703. [Google Scholar] [CrossRef] [PubMed]
 SarmientoReyes, A.; RodríguezVelásquez, Y. Mazesolving with a memristive grid of chargecontrolled memristors. In Proceedings of the 9th Latin American Symposium on Circuits & Systems (LASCAS), Puerto Vallarta, Mexico, 25–28 February 2018; pp. 1–4. [Google Scholar]
 Brown, S.; Pyke, D.; Steenhof, P. Electric vehicles: The role and importance of standards in an emerging market. Energy Policy 2010, 28, 3797–3806. [Google Scholar] [CrossRef]
 Makeblock mBot Mega. Available online: https://www.makeblock.com/pages/mbotmegasmartremotecontrolrobot (accessed on 24 September 2023).
Shortest Path  Processing Time (sec)  Travel Time (sec)  Distance (m)  Battery Consumption (%) 

Figure 3a  1.41  7.88  4.2  0.43 
Figure 3b  2.15  89.75  46.6   
Reference  Basic Algorithm  Maze Size  Robot Size  Scaling Property  Experimental Verification 

[16]  Wall detection  Medium  N  N  N 
[17]  Astart  Small  N  N  Y 
[18]  BreadthFirst Search  Small  N  N  Y 
[19]  Astart  Large  N  N  N 
[20]  Direction Envelope  Small  N  N  N 
[21]  Direction Envelope  Small  N  N  Y 
[22]  Modified Direction Envelope  Small  N  N  N 
This work  BreadthFirst Search  Very Large  Y  Y  Y 
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AvilaSánchez, L.A.; SánchezLópez, C.; OchoaMontiel, R.; MontalvoGalicia, F.; SánchezGaspariano, L.A.; HernándezMejía, C.; GonzálezHernández, H.G. Maze Solving Mobile Robot Based on Image Processing and Graph Theory. Technologies 2023, 11, 171. https://doi.org/10.3390/technologies11060171
AvilaSánchez LA, SánchezLópez C, OchoaMontiel R, MontalvoGalicia F, SánchezGaspariano LA, HernándezMejía C, GonzálezHernández HG. Maze Solving Mobile Robot Based on Image Processing and Graph Theory. Technologies. 2023; 11(6):171. https://doi.org/10.3390/technologies11060171
Chicago/Turabian StyleAvilaSánchez, Luis A., Carlos SánchezLópez, Rocío OchoaMontiel, Fredy MontalvoGalicia, Luis A. SánchezGaspariano, Carlos HernándezMejía, and Hugo G. GonzálezHernández. 2023. "Maze Solving Mobile Robot Based on Image Processing and Graph Theory" Technologies 11, no. 6: 171. https://doi.org/10.3390/technologies11060171