In this paper, we propose a mapping approach that constructs a globally deformable virtual occupancy grid map (VOG-map) based on local submaps. Such a representation allows pose graph SLAM systems to correct globally accumulated drift via loop closures while maintaining free space information for the purpose of path planning. We demonstrate use of such a representation for implementing an underwater SLAM system in which the robot actively plans paths to generate accurate 3D scene reconstructions. We evaluate performance on simulated as well as real-world experiments. Our work furthers capabilities of mobile robots actively mapping and exploring unstructured, three dimensional environments.
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Ho et al. (2018) studied this question.
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