Scan-Point Planning and 3-D Map Building for a 3-D Laser Range Scanner in an Outdoor Environment

During search missions in disaster environments, an important task for mobile robots is map building. An advantage of three-dimensional (3-D) mapping is that it can provide depictions of disaster environments that will support robotic teleoperations used in locating victims and aid rescue crews in strategizing. However, the 3-D scanning of an environment is timeconsuming because a 3-D scanning procedure itself takes a time and scan data must be matched at several locations. Therefore, in this paper, we propose a scan-point planning algorithm to obtain a large scale 3-D map, and we apply a scan-matching method to improve the accuracy of the map. We discuss the use of scan-point planning to maintain the resolution of sensor data and to minimize occlusion areas. The scan-matching method is based on a combination of the Iterative Closest Point (ICP) algorithm and the Normal Distribution Transform (NDT) algorithm.We performed several experiments to verify the validity of our approach.