In this paper, a novel robotic system that solves the problem of autonomous mapping an underfloor void is presented. The approach is based on a 3D laser scanner. A real time navigation system and a new high level planner that selects the next best scanning position controls the motion of the robot. Multiple scans are aligned using ICP and graph optimization techniques. Finally, a point cloud fusion algorithm creates a global model of the environment from the aligned scans. The survey robot has been successfully deployed in a commercial application for scanning underfloor voids before and after the application of thermal insulation. Using this system, the robot was successfully able to autonomously map the controlled test scenario. For some applications the quantity of rubble within the void caused the real time navigation to fail and teleoperation and manual initialization of the ICP algorithm was necessary.