Fuzzy Logic Control for Mobile Robot Navigation in Automated Storage

—Automated Storage (AS) are designed to store and retrieve products in specific locations within manufacturing, warehouses, institutions, and others. These AS involve the usage of robots to move the stored items in and out of the warehouse. However, a challenge for AS systems is to solve the path planning for finding shortest path in a minimum amount of time while avoiding collisions with other robots or static obstacles. Fuzzy Logic systems are widely used in several application areas requiring mimicking the human decision logic under uncertainty. In this paper, we proposed an Automated Storage (AS) robot navigation by using three Fuzzy subsystems combined together to ensure path planning with obstacle avoidance. These three fuzzy subsystems are: Reach Target, Avoid Obstacle, and Escape Cul-De-sac. Therefore, fuzzy rules are employed along with the corresponding defuzzication process to control left and right wheel movement steps of the robot. These systems achieve reaching the goal (using the first subsystem) while avoiding different obstacles on the way (using the second subsystem), even the ones that form a trap (using the third subsystem). These three systems will be used for path planning and following. The overall model was simulated using C# code. The initial results showed the effectiveness of the model in different scenarios: namely no obstacles, static ones, traps, and dynamic obstacles. The path length was comparable to that of traditional shortest path methods such as Dijkstra and A*. The results were also compared to a newer method called APSO. The system’s response was quick due to the fewer needed instructions and reduced memory storage needs. All this was done assuming a constant speed for robots and dynamic obstacles.