Shichao Yang

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This paper addresses the problem of autonomous navigation of a mi-cro aerial vehicle (MAV) inside a constrained shipboard environment for inspection and damage assessment, which might be perilous or inaccessible for humans especially in emergency scenarios. The environment is GPS-denied and visually degraded, containing narrow passageways, doorways and(More)
— We consider the problem of understanding the 3D layout of indoor corridor scenes from a single image in real time. Identifying obstacles such as walls is essential for robot navigation, but also challenging due to the diversity in structure, appearance and illumination of real-world corridor scenes. Many current single-image methods make Manhattan-world(More)
— Existing simultaneous localization and mapping (SLAM) algorithm is not robust in challenging low-texture environments because of few salient features. The resulting sparse or semi-dense map also conveys little information for motion planning. Though some work utilize plane or scene layout for dense map regularization, they require decent state estimation(More)
This paper addresses the problem of autonomous navigation of a micro aerial vehicle (MAV) for inspection and damage assessment inside a constrained shipboard environment, which might be perilous or inaccessible for humans, especially in emergency scenarios. The environment is GPS-denied and visually degraded, containing narrow passageways, doorways, and(More)
— Existing simultaneous localization and mapping (SLAM) algorithms are not robust in challenging low-texture environments because there are only few salient features. The resulting sparse or semi-dense map also conveys little information for motion planning. Though some work utilize plane or scene layout for dense map regularization, they require decent(More)
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