Dynamic path finding method and obstacle avoidance for automated guided vehicle navigation in Industry 4.0
| Autor: | Yigit Can Dundar |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Flexibility (engineering)
Industry 4.0 Computer science Multi-agent system Real-time computing Automated guided vehicle VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420 VDP::Mathematics and natural science: 400::Information and communication science: 420 Scalability Path (graph theory) Obstacle avoidance General Earth and Planetary Sciences Dynamic method General Environmental Science |
| Zdroj: | KES |
| Popis: | Within the scope of Industry 4.0, Automated Guided Vehicles (AGVs) are used to streamline logistics through the usage of efficient path finding methods. The current path finding methods in the industry rely on excessive usage of guidance in the shape of magnets, tapes or QR codes on the floor that the AGVs follow to reach their destinations. However, the current methods lack operational flexibility and are costly to scale in the cases of job-shop floor expansions. In this paper, a dynamic path finding method with obstacle avoidance is presented which utilizes distance measuring sensors to avoid obstacles and reach the goal destination using the most direct path as possible. Tests for functionality and multi-agent scaling have been conducted to evaluate the performance of the dynamic method in a multi-agent setting. The results show that the dynamic method scales properly and is capable of navigating multiple agents through a simulated warehouse environment autonomously and without relying on external guidance. The dynamic method is able to avoid most collisions using distance measuring sensors and multi-agent negotiation to resolve conflicts among the agents that could have resulted in potential collisions. The proposed dynamic method provides a flexible and scalable path finding method for use in Industry 4.0. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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