Abstract
The most vital element in making a non-playable car AI in racing games is finding the shortest path between two locations (the start and the finish lines) by making an efficient algorithm for the car to follow it. Usually, both the lines are predetermined for each race in most of the popular games. However, there has not been any game where the player gets the option to select those. Hence, in this work, an effort will be given to make sure that the player can choose the start line (source) and the finish line (destination) while flood-fill algorithm calculates the shortest path for the car at a shortest possible time and helps the car to follow it fast enough. The completed game has been tested, and from the user review, it seems to be quite difficult to defeat the opponent.
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References
Rautanen A (2018) Designing and Implementing AI for a Car Game. Vaasa University of Applied Sciences
Tjiharjadi S, Setiawan E (2016) Design and implementation of a path finding robot using flood fill algorithm. Int J Mech Eng Robot Res 5(3):180–185
Hossain MS, Das N, Patwary MKH, Al-Hasan M (2018) Finding the nearest blood donors using Dijkstra Algorithm. SISFORMA J Inf Syst 5(2):40–44
Hossain MS, Tanim AS, Nawal N, Akter S (2019) An innovative tour recommendation system using graph algorithms. J Inf Syst Eng Bus Intell 5(1):32–39
Zubov I, Ilya A, Aidar G, Ruslan M, Ilya S (2018) Autonomous drifting control in 3D car racing simulator. In: International conference on intelligent systems (IS), 2018, pp 1–7
Kumar R et al (2016) Maze solving robot with automated obstacle avoidance. Procedia Comput Sci 105:57–61
Bienias Ł, Szczepański K, Duch P (2016) Maze exploration algorithm for small mobile platforms. Image Process Commun 21(3):15–26
Ayad Mohammed Jabbar (2016) Autonomous navigation of mobile robot based on flood fill algorithm. Iraq J Electr Electron Eng 12(1):79–84
Tangasanawit P, Pongphankae S (2017) Search space reduction using adaptive flood filled for path planning in computer games. In: International conference on information technology (INCIT), pp 1–6
Aqel MOA, Issa A, Khdair M, Elhabbash M, Abubaker M, Massoud M (2017) Intelligent maze solving robot based on image processing and graph theory algorithms. In: Proceedings—2017 International Conference Promise Electronic Technology ICPET 2017, pp 48–53
Nyein YM, Win NN (2016) Path finding and turning with maze solving robot. Int J Sci Eng Technol Re. 5(9):2856–2861
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Sabir Hossain, M., Robaitul Islam Bhuiyan, M., Shariful Islam, M., Faridul Islam, M., Al-Hasan, M. (2020). Facilitating Hard-to-Defeat Car AI Using Flood-Fill Algorithm. In: Uddin, M.S., Bansal, J.C. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-3607-6_43
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DOI: https://doi.org/10.1007/978-981-15-3607-6_43
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