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Ibrahim, K., Saad, A., Abo El-Lail, A., Zidane, I. (2025). Development of Path Planning Approach for Mobile Robot In Static Environment. JES. Journal of Engineering Sciences, 53(2), 45-63. doi: 10.21608/jesaun.2025.342727.1388
khalil Ibrahim; Ahmed Saad; Aly S. Abo El-Lail; Issa Zidane. "Development of Path Planning Approach for Mobile Robot In Static Environment". JES. Journal of Engineering Sciences, 53, 2, 2025, 45-63. doi: 10.21608/jesaun.2025.342727.1388
Ibrahim, K., Saad, A., Abo El-Lail, A., Zidane, I. (2025). 'Development of Path Planning Approach for Mobile Robot In Static Environment', JES. Journal of Engineering Sciences, 53(2), pp. 45-63. doi: 10.21608/jesaun.2025.342727.1388
Ibrahim, K., Saad, A., Abo El-Lail, A., Zidane, I. Development of Path Planning Approach for Mobile Robot In Static Environment. JES. Journal of Engineering Sciences, 2025; 53(2): 45-63. doi: 10.21608/jesaun.2025.342727.1388

Development of Path Planning Approach for Mobile Robot In Static Environment

Article 3, Volume 53, Issue 2, March and April 2025, Page 45-63  XML PDF (921.03 K)
Document Type: Research Paper
DOI: 10.21608/jesaun.2025.342727.1388
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Authors
khalil Ibrahim email 1; Ahmed Saad2; Aly S. Abo El-Lail3; Issa Zidane2
1Mechatronics Engineering Dept., Faculty of Engineering, Assiut University, Assiut, Egypt / Faculty of Industry and Energy Technology, New Assiut Technological University (NATU), New Assiut city, Egypt.
2Mechatronics Engineering Dept., Faculty of Engineering, Assiut University, Assiut, Egypt.
3Mechanical Engineering Dept., Faculty of Engineering, Assiut University, Assiut, Egypt.
Abstract
Self-motion Robots and their static environments are the main topics for trajectory planning researchers, especially when the environments contain static and movable obstacles that make the robots' mission harder to reach their target. Therefore, accurate and comprehensive knowledge of autonomous robots' control strategies makes us take the basic steps to build our approach in mobile robot trajectory planning. Accordingly, in this research paper, we will provide an accurate detail of two path planning algorithms A star and 4_sector wavefront algorithms. Some modifications and improvements to its software structure for each algorithm will reduce the time it takes for the robot to reach the desired goal, taking into account the presence of obstacles in the map that is dealt with and how to avoid collision with it, especially dead-end obstacles, which cause the robot to enter into a state of making wrong decisions that can lead to a collision or a significant waste of time required to reach the specified goal. The simulation results of the A-star algorithm and 4_sector wavefront methods using MATLAB program are achieved in different ways using inputs via camera, then image processing is applied to determine the locations of obstacles, starting point, free space, and target point for the robot without any position error. The wavefront algorithm takes a shorter time than the A-star method to reach the final position.
Keywords
Path planning; Image processing; A_star algorithm; Matlab software wavefront method
Main Subjects
Mechanical, Power, Production, Design and Mechatronics Engineering.
References
  1. Hachour, O.: The proposed genetic FPGA implementation for path planning of autonomous mobile robot. Int. J. Circ. Syst. Sig. Process. 2(2), 151–167 (2008)
  2. Jinyu Dai, Jin Qiu, Haocheng Yu, Chunyang Zhang, Zhengtian Wu and Qing GAO: Robot Static Path Planning Method Based on Deterministic Annealing. Machines, Machines 2022, 10(8), 600; www.doi.org/10.3390/machines10080600. (2022)
  3. Ferguson, D., Likhachev, M., Stentz, A.: A guide to heuristic-based path planning. School of Computer Science, Carnegie Mellon University Pittsburgh, PA, USA. American Association for Artificial Intelligence (2005). www.aaai.org.
  4. B.K. Patle a, Ganesh Babu L b, Anish Pandey c, D.R.K. Parhi d, A. Jagadeesh: A review: On path planning strategies for navigation of mobile robot. Production and hosting by Elsevier B.V. on behalf of China Ordnance Society, 2214-9147, (2019). https://doi.org/10.1016/j.dt.2019.04.011.
  5. Sariff, N., Buniyamin, N.: An overview of autonomous mobile robot path planning algorithms. In: Proceedings of 4th Student Conference on Research and Development, pp. 183–188 (2006).
  6. Chao Liu , Lei Wu , Guangxin Li, Hao Zhang, Wensheng Xiao, Dengpan Xu, Jingjing Guo, Wentao Li "  Improved multi-search strategy A* algorithm to solve three-dimensional pipe routing design" Expert Systems with Applications Volume 240, 15 April 2024.
  7. Reddy, H.: Path Finding - Dijkstra’s and A* Algorithm’s, 13 December (2013).
  8. David Ball,Ben Upcroft, Gordon Wyeth, Peter Corke, Andrew English, Patrick Ross, Tim Patten, Robert Fitch, Salah Sukkarieh, Andrew Bate: Vision-based Obstacle Detection and Navigation for an Agricultural Robot. Journal of Field Robotics 33(8), 1107–1130, DOI: 10.1002/rob.21644. Australia, (2016).
  9. Y. Wang, B. Du, Y. Shen, K. Wu, G. Zhao, J. Sun, and H. When: “EV-gait: Event-based robust gait recognition using dynamic vision sensors,” in Proc. IEEE Conf. Computer Vision and Pattern Recognition (CVPR), June 2019, pp. 6351– 6360. Doi: 10.1109/CVPR.2019.00652.
  10. Yuncheng Lu, Zhucun Xue, Gui-Song Xia & Liangpei Zhang,” A survey on vision-based UAV navigation”, Geo-spatial Information Science, 21:1, 21-32, DOI: 10.1080/10095020.2017.1420509, (2018).
  11. Chandak, A., Gosavi, K., Giri, S., Agrawal, S., Kulkarni, P.: Path planning for mobile robot navigation using image processing. Int. J. Sci. Eng. Res. 4(6), 1490–1495 (2013).
  12. S. Aggarwal and N. Kumar: “Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges”, Computer Communications, S0140-3664(19)30853-9, (2019), Doi: https://doi.org/10.1016/j.comcom.2019.10.014.
  13. Fernando Perez-Sanz, Pedro J. Navarro and Marcos Egea-Cortines,” Plant phenomics: an overview of image acquisition technologies and image data analysis algorithms”, Giga Science, Volume 6, Issue 11, November 2017, gix092, Doi: 10.1093/gigascience/gix092.
  14. Shojaeipour, S., et al.: Vision-based mobile robot navigation using image processing and cell decomposition. In: IVIC 2009. LNCS, vol. 5857, pp. 90–96 (2009).
  15. Campbell, J., Sukthankar, R., Nourbakhsh, I., Pahwa, A.: A robust visual odometry and precipice detection system using consumer-grade monocular vision. In: Proceedings of ICRA 2005, Barcelona, Spain (2005).
  16. Fábio Celestino Pereira, Carlos Eduardo Pereira,” Embedded Image Processing Systems for Automatic Recognition of Cracks using UAVs”, IFAC-Papers Online, Volume 48, Issue 10, 2015, Pages 16-21, https://doi.org/10.1016/j.ifacol.2015.08.101.
  17. ChenSunaChenTangaXinjunZhuaXiaoyuLiaLinlinWangb, “An efficient method for salt-and-pepper noise removal based on shearlet transform and noise detection”, AEU - International Journal of Electronics and Communications, 1434-8411, Volume 69, Issue 12, December 2015, Pages 1823-1832, http://dx.doi.org/10.1016/j.aeue.2015.09.007.
  18. Wenzhou GAO, Lei Yang, Xiaoguang Zhang, Huizhong Liu, “An Improved Sobel Edge Detection”, 978-1-4244-5540-IEEE, 3rd International Conference on Computer Science and Information Technology, Chenddu, China, pp. 67-71, 2010.
  19. Akshay Kumar Guruji, Himansh Agarwal, D. K. Parsediya,” Time-Efficient A* Algorithm for Robot Path Planning”, 3rd International Conference on Innovations in Automation and Mechatronics Engineering, Ahmedabad, India, Published by Elsevier Journal, pp.144-149, ICIAME 2016.
  20. Basem M. ElHalawany, HalaM. Abdel-Kader, AdlyTagEldeen, AlaaEldeenElsayed, ZakiB. Nossair,” Modified A* Algorithm for Safer Mobile Robot Navigation”, U2013 Proceedings of International Conference on Modelling, Identification & Control (ICMIC) Cairo, Egypt, 31st Aug- 2ndSept,pp.74-78,2013.
  21. FrantišekDucho, Andrej Babineca, Martin Kajana, Peter Beoa, Martin Floreka, TomášFicoa, LadislavJurišicaa, “Path planning with modified A star algorithm for a mobile robot”, Published by Elsevier Journal, Procedia Engineering 96, pp. 59-69, 2014.
  22. C.Wang, L.Wang, and J.Qin, X.Su, W.Li, Z. Lu, and M.Li, Z.Wu, L.Duan, Z.Li, M.Cao and XicuiOu, Y.Wang, J.Long, M.Huang, Y.Li and Q.Wang, “Path Planning of Automated Guided Vehicles Based on Improved A-Star Algorithm”, Proceeding of the 2015 IEEE International Conference on Information and Automation, Lijiang, China, pp.2071-2076, August 2015.
  23. Haifeng Wang, Jiawei Zhou, GuifengZheng, Yun Liang, “HAS: Hierarchical A-Star Algorithm for Big Map Navigation in Special Areas”, International Conference on Digital Home, pp.222-225, Guangzhou, China, 2014.
  24. Abdel-Nasser Sharkawy "Task Location to Improve Human–Robot Cooperation: A Condition Number-Based Approach" Automation, Vol.  4, pp. 263–290, 2023.
  25. Martin Psotka, František Ducho  , Mykhailyshyn Roman, Tölgyessy Michal  and Dobiš Michal " Global Path Planning Method Based on a Modification of the Wavefront Algorithm for Ground Mobile Robots " Robotics, Vol. 25,pp.1-16 2023.
  26. Zhang, B.; Li, G.; Zheng, Q.; Bai, X.; Ding, Y.; Khan, A. Path planning for wheeled mobile robot in partially known uneven terrain. Sensors 2022, 22, 5217.
  27. Looi, C.Z.; Ng, D.W.K. A Study on the Effect of Parameters for ROS Motion Planer and Navigation System for Indoor Robot. Int. J. Electr. Comput. Eng. Res. 2021, 1, 29–36.
  28. Aggarwal, S.; Kumar, N. Path planning techniques for unmanned aerial vehicles: A review, solutions, and challenges. Computer Communications, 2020, 149, 270–299.
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