Multiple-AGV Path Planning Method for Two Industrial Links

Nowadays, increasing automatic guided vehicles (AGVs) are being introduced into the production line. The path planning and scheduling of multiple AGVs are complex tasks that are closely related to application scenarios. In this study, a robot’s working area was divided to minimize the collision probability. Improved ant colony optimization (ACO) and improved probabilistic road map (PRM) algorithms were used for path planning to enhance the transportation efficiency. The priorities of AGVs were specified. The collision criteria were determined, and the responses for different collision types were provided.