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Monocular visual-inertial odometry leveraging point-line features with structural constraints
Structural geometry constraints, such as perpendicularity, parallelism and coplanarity, are widely existing in man-made scene, especially in...
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Improved monocular visual-inertial odometry with point and line features using adaptive line feature extraction
With the development of intelligent era, the application of UAVs is more and more extensive, and positioning and navigation technology is the key....
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A Lightweight Sensor Fusion for Neural Visual Inertial Odometry
In recent years, the performance of visual inertial odometry (VIO) based on deep learning has shown significant advantages over traditional geometric...
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Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality Selection
In recent years, deep learning-based approaches for visual-inertial odometry (VIO) have shown remarkable performance outperforming traditional...
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Visual Inertial Navigation Optimization Method Based on Landmark Recognition
This study utilizes a low-cost, low-power, and highly accurate monocular visual-inertial odometry (VIO) as the navigation algorithm for unmanned...
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Renormalization for Initialization of Rolling Shutter Visual-Inertial Odometry
In this paper we deal with the initialization problem of a visual-inertial odometry system with rolling shutter cameras. Initialization is a...
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Robust stereo inertial odometry based on self-supervised feature points
In the application of intelligent mobile robots, the odometry is the key system for implementing positioning. Traditional feature extraction...
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R-SDSO: Robust stereo direct sparse odometry
This paper presents a robust stereo direct visual odometry method with improved robustness against drastic brightness variation and aggressive...
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Learned Monocular Depth Priors in Visual-Inertial Initialization
Visual-inertial odometry (VIO) is the pose estimation backbone for most AR/VR and autonomous robotic systems today, in both academia and industry....
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A Visual Inertial SLAM Method for Fusing Point and Line Features
The current SLAM methods generally have some drawbacks: such as poor stability and long time-consuming SLAM tasks; in order to solve the problem of...
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VI-NeRF-SLAM: a real-time visual–inertial SLAM with NeRF map**
In numerous robotic and autonomous driving tasks, traditional visual SLAM algorithms estimate the camera’s position in a scene through sparse feature...
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Information-Theoretic Odometry Learning
In this paper, we propose a unified information theoretic framework for learning-motivated methods aimed at odometry estimation, a crucial component...
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Replay-Based Online Adaptation for Unsupervised Deep Visual Odometry
Online adaptation is a promising paradigm that enables dynamic adaptation to new environments. In recent years, there has been a growing interest in...
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Accurate and robust odometry by fusing monocular visual, inertial, and wheel encoder
Tracking the pose of a robot has been gaining importance in the field of Robotics, e.g., paving the way for robot navigation. In recent years,...
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Improving visual odometry pipeline with feedback from forward and backward motion estimates
Estimating motion from visual cameras has become a promising art in the area of autonomous navigation and constant efforts are being made toward...
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A Visual-Inertial Fusion Map** and Localization System Using AprilTag in GNSS-Denied Scenes
This paper addresses the challenge of achieving precise and long-term positioning for vehicles in GNSS-denied scenes such as indoor parking lots. To...
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Fusion of visual odometry and place recognition for SLAM in extreme conditions
Simultaneous Localization and Map** (SLAM) under extreme conditions like unsuitable lightning conditions and adversarial weather conditions (fog,...
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Loosely-coupled lidar-inertial odometry and map** in real time
The lidar-inertial-based simultaneous localization and map** (SLAM) have been widely investigated in recent years. In this paper, a loosely-coupled...
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Outlier Detection for Visual Odometry in Vegetated Scenes Using Local Flow Consistency
We present a novel outlier detector for visual odometry algorithms operating in dynamic vegetated environments. The outlier detector utilises the...
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MAIM-VO: A Robust Visual Odometry with Mixed MLP for Weak Textured Environment
Visual localization is a critical technology for visual SLAM systems, which determines the relative position and motion trajectory by tracking...