Academic Journal
Enhancing A-Star Algorithm Efficiency using Node Reduction Optimization of Flood Algorithm: Autonomous Navigation in Port Inspection Robot
| العنوان: | Enhancing A-Star Algorithm Efficiency using Node Reduction Optimization of Flood Algorithm: Autonomous Navigation in Port Inspection Robot |
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| المؤلفون: | Wardana, Hartanto Kusuma, Rumaksari, Atyanta Nika, Picanussa, Prischa Wilhelmina, Murtianta, Budihardja, Sooai, Adri Gabriel, Recto, King Harold |
| المساهمون: | Universitas Kristen Satya Wacana |
| المصدر: | International Journal of Artificial Intelligence Research; Vol 8, No 1 (2024): June 2024 ; 2579-7298 ; 10.29099/ijair.v8i1 |
| بيانات النشر: | STMIK Dharma Wacana |
| سنة النشر: | 2024 |
| المجموعة: | International Journal of artificial intelligence research (IJAIR) |
| مصطلحات موضوعية: | Artificial Intelligence, Artificial Intelligence on Robotic Application, Optimization A-star Algorithm, Flood Algorithm, Autonomous Navigated, Inspection Robot, Path Planning Efficiency |
| الوصف: | Research on automatic port inspections using robots has been carried out in The state-owned company Indonesia Port Corporation, Semarang Indonesia. However, increasing the efficiency of robotic inspections is critical because robots need to perform these tasks with much higher speeds than humans, while maintaining a high level of accuracy. The robot is equipped with sensors and computer vision technology to detect defects or problems that the human might miss. This aim is to increase overall inspection accuracy at a lower cost. In this research, we introduce an optimized A-star path planning algorithm that incorporating with the flood algorithm, node reductions process, and linear path planning optimization for an autonomous navigated port inspection robot. Our primary objective is to significantly increase the efficiency of the conventional A-star algorithm in guiding robotic systems through complex paths. The proposed algorithm demonstrates exceptional efficiency in generating feasible paths, with success attributed to optimization steps that specifically target reducing node processing and enhancing route finding. The experimentation phase involves a comprehensive assessment of the algorithm using six key parameters: running time, number of nodes, number of turns, maximum turning angle, expansion nodes, and the total distances output. Through rigorous testing, the algorithm's performance is evaluated and compared against seven other algorithms, namely A-star, BestFirst, Dijkstra, BFS, DFS, Bidirectional A-star, and Geometric A-star. Results from the experiments reveal the algorithm's outstanding running time efficiency, surpassing all other algorithms tested. Notably, it exhibits a remarkable 6.5% improvement over the widely recognized Geometric A-star algorithm. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | http://ijair.id/index.php/ijair/article/view/1152 |
| DOI: | 10.29099/ijair.v8i1.1152 |
| الاتاحة: | http://ijair.id/index.php/ijair/article/view/1152 https://doi.org/10.29099/ijair.v8i1.1152 |
| Rights: | Copyright (c) 2024 International Journal of Artificial Intelligence Research ; https://creativecommons.org/licenses/by-sa/4.0 |
| رقم الانضمام: | edsbas.A0589CA9 |
| قاعدة البيانات: | BASE |
| DOI: | 10.29099/ijair.v8i1.1152 |
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