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.
CITATION STYLE
Nagatani, K., Matsuzawa, T., & Yoshida, K. (2010). Scan-point planning and 3-D map building for a 3-D laser range scanner in an outdoor environment. Springer Tracts in Advanced Robotics, 62, 207–217. https://doi.org/10.1007/978-3-642-13408-1_19
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