Adaptive warning fields for warehouse AGVs

AGV (automated guided vehicle) systems are extensively used in factory and warehouse environments. As most of these environments employ a mix of AGVs, manually driven vehicles, and human workers, safety is an important subject. Current AGV systems employ safety fields and laser scanners to ensure safety in their environments. These fields however are often primitive and do not take into account future AGV trajectory or intentions of agents in their vicinity. This results in inefficient operation of such AGVs. We propose a three-layered architecture that consists of safety fields that are formed around immediate future trajectory of AGV as well as on the predicted intention of an agent in AGV vicinity, resulting in more efficient AGV behaviour. Results are presented using real laser data from a small-sized lab AGV as well as an industrial forklift truck.