15 accepted papers
In this paper, we present an efficient and robust GPS-aided visual inertial odometry (GPS-VIO) system that fuses IMU-camera data with intermittent GPS measurements. To perform sensor fusion, spatiotemporal sensor calibration and initialization of the transform between the sensor reference frames are…
In this paper, we present an open platform, termed OpenVINS, for visual-inertial estimation research for both the academic community and practitioners from industry. The open sourced codebase provides a foundation for researchers and engineers to quickly start developing new capabilities for their v…
In this paper we investigate the effect of tightly-coupled estimation on the performance of visual-inertial localization and dynamic object pose tracking. In particular, we show that while a joint estimation system outperforms its decoupled counterpart when given a "proper" model for the target's mo…
In this paper, we introduce a novel visual-inertial-wheel odometry (VIWO) system for ground vehicles, which efficiently fuses multi-modal visual, inertial and 2D wheel odometry measurements in a sliding-window filtering fashion. As multi-sensor fusion requires both intrinsic and extrinsic (spatiotem…
Enabling real-time visual-inertial navigation in unknown environments while achieving bounded-error performance holds great potentials in robotic applications. To this end, in this paper, we propose a novel linear-complexity EKF for visual-inertial localization, which can efficiently utilize loop cl…
In this letter, we perform in-depth observability analysis for both spatial and temporal calibration parameters of an aided inertial navigation system (INS) with global and/or local sensing modalities. In particular, we analytically show that both spatial and temporal calibration parameters are obse
This paper presents a general multi-camera visual-inertial navigation system (mc-VINS) with online instrinsic and extrinsic calibration, which is able to utilize all the information from an arbitrary number of asynchronous cameras. In particular, within the standard multi-state constraint Kalman Fil…
In this paper, we present a real-time multi-IMU visual-inertial navigation system (mi-VINS) that utilizes the information from multiple inertial measurement units (IMUs) and thus is resilient to IMU sensor failures. In particular, in the proposed mi-VINS formulation, one of the IMUs serves as the “b…
This paper presents a tightly-coupled aided inertial navigation system (INS) with point and plane features, a general sensor fusion framework applicable to any visual and depth sensor (e.g., RGBD, LiDAR) configuration, in which the camera is used for point feature tracking and depth sensor for plane…
In this letter we present a novel method to perform target tracking of a moving rigid body utilizing an inertial measurement unit with cameras. A key contribution is the tightly-coupling of the target motion estimation within a visual-inertial navigation system (VINS), allowing for improved performa
In this paper, we present a tightly-coupled monocular visual-inertial navigation system (VINS) using points and lines with degenerate motion analysis for 3D line triangulation. Based on line segment measurements from images, we propose two sliding window based 3D line triangulation algorithms and co…
In this paper, we address the problem of optimally fusing multiple heterogeneous and asynchronous sensors for use in 3D mapping and localization of autonomous vehicles. To this end, based on the factor graph-based optimization framework, we design a modular sensor-fusion system that allows for effic…
This paper presents the formalization of the closest point plane representation and an analysis of its incorporation in 3D indoor simultaneous localization and mapping (SLAM). We present a singularity free plane factor leveraging the closest point plane representation, and demonstrate its fusion wit…
Recent advancements in the performance and affordability of cameras and inertial measurement units (IMUs) have caused demand for efficient, accurate visual-inertial navigation solutions. In this paper, we present a system for the fusion of preintegrated inertial measurements with highly informative…
Graph-based SLAM approaches have had success recently despite suffering from ever-increasing computational costs due to the need of optimizing over the entire robot trajectory. To address this issue, in this paper, we advocate the decoupling of marginalization (node removal) and sparsification (edge…