LIRS-USim: a Gazebo-based Tool for Modeling Urban Environments and Sensory Data Uncertainties

Urban Search and Rescue (USAR) robotics deals with emergent situations that occur in urban environments due to natural and human-made disasters. To support early stages of algorithms’ testing and evaluation, we developed an easy to use USAR simulation tool (LIRS-USim) that models typical USAR missions within the Gazebo simulator. The proposed robot operating system based tool is capable of modeling a virtual environment with hazardous zones, constructing a 3D Gazebo world from an arbitrary 2D image and populating it with various obstacles from the Gazebo library, simulating uncertainties and failures of robot’s onboard sensors. To set up a hazardous zone, its location, size and a radiation or chemical contamination shape are defined by a user. Next, any existing in Gazebo robot model with any onboard sensors could be loaded into the 3D world, and probabilities of each sensor uncertainty and failure could be set individually by a user. Moreover, LIRS-USim allows loading several robots of different types into a single Gazebo world and further monitor each robot and each sensor. LIRS-USim was successfully tested with Husky, Warthog, Jackal, and Hector Quadrotor standard robot models. The source code of LIRS-USim is available for free academic use.