Abstract
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.
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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. In: Howard, A., Iagnemma, K., Kelly, A. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13408-1_19
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DOI: https://doi.org/10.1007/978-3-642-13408-1_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13407-4
Online ISBN: 978-3-642-13408-1
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