This paper presents a mapping method that can accurately map large environment with one single robot by visiting the environment for only once, and the resulting map can provide thorough 3D description for the environment in a predefined global coordinate system. Our first contribution is to represent the map as a collection of submaps arranged in a deformable configuration, and to perform loop-closing by registering this submap configuration to an aerial image. The second contribution is to introduce the active contour technique to the SLAM domain, so that the registration is efficiently solved in an iterative energy minimization process. The constraints from robot mapping are modeled as forces trying to keep the submaps consistent to each other, while the pictorial matching is represented by forces guiding submaps to a configuration consistent with the aerial image. In the experiment, we demonstrate the proposed algorithm's capability to close a 1,890 meters loop with only one visiting. The result is compared with ground truth, and high accuracy is observed.
REF use an energy minimization technique to merge prior information from aerial images and mapping.
Large-Scale Loop-Closing by Fusing Range Data and Aerial Image
Int. J. Robotics Autom.
Int. J. Robotics Autom.
Computer Science Engineering