8 accepted papers
In this work, we present a novel method for reconstructing particular 3D surface points using an imaging sonar sensor. We derive the two-dimensional Fermat flow equation, which may be applied to the planes defined by each discrete azimuth angle in the sonar image. We show that the Fermat flow equati…
We present a novel framework for object-level 3D underwater reconstruction using imaging sonar sensors. We demonstrate that imaging sonar reconstruction is analogous to the problem of confocal non-line-of-sight (NLOS) reconstruction. Drawing upon this connection, we formulate the problem as one of s…
In this letter, we propose a novel method for underwater localization using natural visual landmarks above the water surface. High-accuracy, drift-free pose estimates are necessary for inspection tasks in underwater indoor environments, such as nuclear spent pools. Inaccuracies in robot localization
In this paper we propose a new framework for reconstructing underwater surfaces from wide aperture imaging sonar sequences. We demonstrate that when the leading object edge in each sonar image can be accurately triangulated in 3D, the remaining surface may be “filled in” using a generative sensor mo…
In this work, we develop a novel dense planar-inertial SLAM (DPI-SLAM) system to reconstruct dense 3D models of large indoor environments using a hand-held RGB-D sensor and an inertial measurement unit (IMU). The preinte-grated IMU measurements are loosely-coupled with the dense visual odometry (VO)…
Recent algorithms have demonstrated the feasibility of underwater feature-based SLAM using imaging sonar. But previous methods have either relied on manual feature extraction and correspondence or used prior knowledge of the scene, such as the planar scene assumption. Our proposed system provides a…
In this paper, we present a novel approach to tightly couple visual and inertial measurements in a fixed-lag visual-inertial odometry (VIO) framework using information sparsification. To bound computational complexity, fixed-lag smoothers typically marginalize out variables, but consequently introdu…
In this work, we develop a novel keyframe-based dense planar SLAM (KDP-SLAM) system, based on CPU only, to reconstruct large indoor environments in real-time using a hand-held RGB-D sensor. Our keyframe-based approach applies a fast dense method to estimate odometry, fuses depth measurements from sm…