Results 181 to 190 of about 23,972 (233)

CMIF-VIO: A Novel Cross Modal Interaction Framework for Visual Inertial Odometry

IEEE Robotics and Automation Letters
Visual Inertial Odometry (VIO) estimates predicted trajectories through self motion. With the popularization of artificial intelligence, deep learning-based VIO methods have shown better performance than traditional geometry-based VIO methods.
Zhenyu Wang, Yunzhou Zhang, Xiao Xu, Mengchen Xiong, Xin Su, Fanle Meng   +5 more
semanticscholar   +1 more source

BotVIO: A Lightweight Transformer-Based Visual–Inertial Odometry for Robotics

IEEE Transactions on robotics
Visual–inertial odometry (VIO) provides a robust localization solution for simultaneous localization and mapping systems. Self-supervised VIO, a leading approach, has the advantage of not requiring extensive ground-truth labels.
Wenhui Wei, Yangfan Zhou, Yimin Hu, Zhi Li, Sen Wang, Xin Liu, Jiadong Li   +6 more
semanticscholar   +1 more source

XR-VIO: High-precision Visual Inertial Odometry with Fast Initialization for XR Applications

arXiv.org
This paper presents a novel approach to Visual Inertial Odometry (VIO), focusing on the initialization and feature matching modules. Existing methods for initialization often suffer from either poor stability in visual Structure from Motion (SfM) or ...
Shangjin Zhai, Nan Wang, Xiaomeng Wang, Danpeng Chen, Weijian Xie, Hujun Bao, Guofeng Zhang   +6 more
semanticscholar   +1 more source

Information Sparsification in Visual-Inertial Odometry

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018
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 introduce a densely connected linear prior which ...
Jerry Hsiung, Ming Hsiao, Eric Westman, Rafael Valencia, Michael Kaess   +4 more
openaire   +1 more source

Enhancing Visual-Inertial Odometry Robustness and Accuracy in Challenging Environments

Robotics
Visual–Inertial Odometry (VIO) algorithms are widely adopted for autonomous drone navigation in GNSS-denied environments. However, conventional monocular and stereo VIO setups often lack robustness under challenging environmental conditions or during ...
Alessandro Minervini, Adrian Carrio, Giorgio Guglieri   +2 more
semanticscholar   +1 more source

DFF-VIO: A General Dynamic Feature Fused Monocular Visual-Inertial Odometry

IEEE transactions on circuits and systems for video technology (Print)
Integrating dynamic effects has shown its significance in enhancing the accuracy and robustness of Visual-Inertial Odometry (VIO) systems in dynamic scenarios.
Nan Luo, Zhexuan Hu, Yuan Ding, Jiaxu Li, Hui Zhao, Gang Liu, Quan Wang   +6 more
semanticscholar   +1 more source

Monocular Visual-Inertial Odometry Based on Local Maximum A Posteriori Estimation

IEEE Robotics and Automation Letters
Monocular visual-inertial odometry can effectively solve the problem of unobservable metric scale in monocular odometry. However, due to differences in sensor observation noise and redundant constraints, the positioning accuracy of a general monocular ...
Bipeng Ye, Guanghong Gong, Ni Li, Yunbo Gao, Tiantian Zhang, Guoqing Hou   +5 more
semanticscholar   +1 more source

Photometric patch-based visual-inertial odometry

2017 IEEE International Conference on Robotics and Automation (ICRA), 2017
In this paper we present a novel direct visual-inertial odometry algorithm, for estimating motion in unknown environments. The algorithm utilizes image patches extracted around image features, and formulates measurement residuals in the image intensity space directly.
Xing Zheng, Zack Moratto, Mingyang Li, Anastasios I. Mourikis   +3 more
openaire   +1 more source

LVIO-Fusion:Tightly-Coupled LiDAR-Visual-Inertial Odometry and Mapping in Degenerate Environments

IEEE Robotics and Automation Letters
In this letter, we present an innovative, tightly-coupled LiDAR-Visual-Inertial Odometry and Mapping framework, termed LVIO-Fusion, which achives robust and precise state estimation and map construction in environments characterized by LiDAR-degenerated ...
Hongkai Zhang, Liang Du, Sheng Bao, Jianjun Yuan, Shugen Ma   +4 more
semanticscholar   +1 more source

360-VIO: A Robust Visual–Inertial Odometry Using a 360° Camera

IEEE transactions on industrial electronics (1982. Print)
Visual–inertial odometry (VIO) is an important component for robots working in industrial environments to obtain accurate and robust pose estimation. In this article, we introduce a novel VIO algorithm designed specifically for 360° cameras, exploiting ...
Qi Wu, Xiangyu Xu, Xieyuanli Chen, Ling Pei, Chao Long, Junyuan Deng, Guoqing Liu, Shengjie Yang, Shilei Wen, Wenxian Yu   +9 more
semanticscholar   +1 more source