Search Results for author:
Found 13 papers, 4 papers with code
Multi-Visual-Inertial System: Analysis, Calibration and Estimation
To this end, we develop a new analytic combined IMU integration with intrinsics-termed ACI3-to preintegrate IMU measurements, which is leveraged to fuse auxiliary IMUs and(or) gyroscopes alongside a base IMU.
General Place Recognition Survey: Towards the Real-world Autonomy Age
A summary of this work and our datasets and evaluation API is publicly available to the robotics community at: https://github. com/MetaSLAM/GPRS.
Loop Closure Detection
Simultaneous Localization and Mapping
Distributed Visual-Inertial Cooperative Localization
In this paper we present a consistent and distributed state estimator for multi-robot cooperative localization (CL) which efficiently fuses environmental features and loop-closure constraints across time and robots.
CodeVIO: Visual-Inertial Odometry with Learned Optimizable Dense Depth
In this work, we present a lightweight, tightly-coupled deep depth network and visual-inertial odometry (VIO) system, which can provide accurate state estimates and dense depth maps of the immediate surroundings.
LIC-Fusion 2.0: LiDAR-Inertial-Camera Odometry with Sliding-Window Plane-Feature Tracking
Only the tracked planar points belonging to the same plane will be used for plane initialization, which makes the plane extraction efficient and robust.
Robotics
MIMC-VINS: A Versatile and Resilient Multi-IMU Multi-Camera Visual-Inertial Navigation System
As cameras and inertial sensors are becoming ubiquitous in mobile devices and robots, it holds great potential to design visual-inertial navigation systems (VINS) for efficient versatile 3D motion tracking which utilize any (multiple) available cameras and inertial measurement units (IMUs) and are resilient to sensor failures or measurement depletion.
Visual-Inertial Localization for Skid-Steering Robots with Kinematic Constraints
While visual localization or SLAM has witnessed great progress in past decades, when deploying it on a mobile robot in practice, few works have explicitly considered the kinematic (or dynamic) constraints of the real robotic system when designing state estimators.
LIC-Fusion: LiDAR-Inertial-Camera Odometry
This paper presents a tightly-coupled multi-sensor fusion algorithm termed LiDAR-inertial-camera fusion (LIC-Fusion), which efficiently fuses IMU measurements, sparse visual features, and extracted LiDAR points.
Robotics
An Efficient Schmidt-EKF for 3D Visual-Inertial SLAM
It holds great implications for practical applications to enable centimeter-accuracy positioning for mobile and wearable sensor systems.
Lightweight Unsupervised Deep Loop Closure
Robust efficient loop closure detection is essential for large-scale real-time SLAM.
Robotics 68T40 I.2.9; I.2.6; I.2.10; I.4; I.5
Robocentric Visual-Inertial Odometry
In this paper, we propose a novel robocentric formulation of the visual-inertial navigation system (VINS) within a sliding-window filtering framework and design an efficient, lightweight, robocentric visual-inertial odometry (R-VIO) algorithm for consistent motion tracking even in challenging environments using only a monocular camera and a 6-axis IMU.
Robotics
Continuous Preintegration Theory for Graph-based Visual-Inertial Navigation
In this paper we propose a new continuous preintegration theory for graph-based sensor fusion with an inertial measurement unit (IMU) and a camera (or other aiding sensors).
Robotics
Robust Visual SLAM with Point and Line Features
In this paper, we develop a robust efficient visual SLAM system that utilizes heterogeneous point and line features.
