CVI-SLAM—Collaborative Visual-Inertial SLAM

The case for visual-inertial SLAM over visual SLAM

Asynchronous Adaptive Conditioning for Visual-Inertial SLAM

This paper is concerned with real-time monocular visual inertial simultaneous localization and mapping (VI-SLAM). In particular a tightly coupled nonlinear-optimization based solution that can match the global optimal result in real time is proposed. The methodology is motivated by the requirement to produce a scale-correct visual map, in an optimization framework that is able to incorporate re...

Large Scale Dense Visual Inertial SLAM

In this paper we present a novel large scale SLAM system that combines dense stereo vision with inertial tracking. The system divides space into a grid and efficiently allocates GPU memory only when there is surface information within a grid cell. A rolling grid approach allows the system to work for large scale outdoor SLAM. A dense visual inertial dense tracking pipeline incrementally localiz...

Monocular Visual-Inertial SLAM: Continuous Preintegration and Reliable Initialization

In this paper, we propose a new visual-inertial Simultaneous Localization and Mapping (SLAM) algorithm. With the tightly coupled sensor fusion of a global shutter monocular camera and a low-cost Inertial Measurement Unit (IMU), this algorithm is able to achieve robust and real-time estimates of the sensor poses in unknown environment. To address the real-time visual-inertial fusion problem, we ...

Towards visual-inertial SLAM for mobile augmented reality

The basic idea of augmented reality is to augment the view of a user or camera with virtual objects. Real-time camera tracking is an enabling technology for augmented reality. Besides the high estimation precision that is needed to allow for pixel accurate augmentations, mobile augmented reality applications impose further requirements on the tracking method. One important aspect is robustness ...