Modular, Risk-Aware Mapping and Fusion of Environmental Hazards

Abstract

Field and service robots that do not understand the hazards in their environment limit their potential by acting overly careful or navigating into potentially dangerous areas. We present an extended modular mapping framework which allows to model different types of hazards from a multitude of inputs. The proposed approach is generalized for storage of arbitrary data, therefore not limiting the usage to one use case. Furthermore the framework allows the fusion of risks to calculate the overall risk for an individual robot from its surroundings. The system was tested with LAURON V, a hexapod designed for walking over rough and hazardous terrain.