Finding Disaster Victims: A Sensory System for Robot-Assisted 3D Mapping of Urban Search and Rescue Environments

In this paper the first application of utilizing a unique 3D real-time mapping sensor for sequential 3D map building within a visual simultaneous localization and mapping (SLAM) framework in unknown cluttered urban search and rescue (USAR) environments is proposed. The sensor utilizes a digital fringe projection and phase shifting technique to provide real-time 2D and 3D sensory information of the environment. The proposed sensor is unique over current technologies, in that it can directly map rubble in 3D and in real-time at a frame rate of up to 60 fps. Furthermore, we propose the development of a novel 3D visual SLAM method utilizing both 2D and 3D images taken by the sensor for robust and reliable landmark identification, mapping and localization algorithms utilizing a scale invariant feature transform (SIFT)-based approach. Preliminary experiments show the potential of the proposed 3D real-time sensory system for such unknown cluttered USAR environments.