Development and Validation of a Digital Twin for a Commercial Mobile Robot

In recent decades, there has been a significant increase in the presence of robots in the daily operations of industries. Automated Guided Vehicles (AGVs) used in industrial environments are gaining prominence due to their numerous applications, ranging from logistic tasks such as material transport to more complex process tasks like replacing conveyor belts in production lines. For a mobile robot to operate in these environments, it must possess skills to perform its functions and ensure safety. In this regard, simulating a computational model of a real autonomous system can contribute to developing new operational strategies. The objective of this work is to explore the use of a Digital Twin for an Automated Guided Vehicle (AGV), aiming to design and validate navigation and obstacle avoidance algorithms, with the intent to optimize the operation of these devices in industrial environments. In the current study, the AGV G3R1000 was used, which was modeled in detail in FUSION 360 software, along with a production line from the AGVS company in Brazil. As validation, the digital robot was used to design the navigation software using the PID control system and obstacle avoidance using Fuzzy control. The algorithm developed in the digital robot was applied to the real robot, and a performance comparison was made. In conclusion, it is possible to use the simulated robot to design algorithms for the real robot, saving resources such as time and equipment.