Dynamic path finding method and obstacle avoidance for automated guided vehicle navigation in Industry 4.0

Abstract Within the scope of Industry 4.0, Automated Guided Vehicles (AGVs) are used to streamline logistics through usage efficient path finding methods. The current methods in industry rely on excessive guidance shape magnets, tapes or QR codes floor that AGVs follow reach their destinations. However, lack operational flexibility and costly scale cases job-shop expansions. In this paper, a dynamic method with obstacle avoidance is presented which utilizes distance measuring sensors avoid obstacles goal destination using most direct as possible. Tests for functionality multi-agent scaling have been conducted evaluate performance setting. results show scales properly capable navigating multiple agents simulated warehouse environment autonomously without relying external guidance. able collisions negotiation resolve conflicts among could resulted potential collisions. proposed provides flexible scalable use 4.0.