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Pose estimation by Omnidirectional Visual-Inertial Odometry [PDF]
Robotics and Autonomous Systems, 2018 Abstract In this paper, a novel approach to ego-motion estimation is proposed based on visual and inertial sensors, named Omnidirectional Visual-Inertial Odometry (OVIO). The proposed approach combines omnidirectional visual features with inertial measurements within the Multi-State Constraint Kalman Filter (MSCKF).
Milad Ramezani +2 more
exaly +4 more sources
DeepTIO: A Deep Thermal-Inertial Odometry With Visual Hallucination [PDF]
IEEE Robotics and Automation Letters, 2020 Accepted to IEEE Robotics and Automation Letters (RAL)
Muhamad Risqi U Saputra +2 more
exaly +9 more sources
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Cooperative Visual-Inertial Odometry
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021This paper studies the problem of multi-robot cooperative visual-inertial localization where each robot is equipped with only a single camera and IMU. We develop two cooperative visual-inertial odometry (C-VIO) algorithms within the multi-state constraint Kalman filter (MSCKF) framework, in which each robot utilizes not only its own measurements but ...
Pengxiang Zhu +3 more
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ATVIO: Attention Guided Visual-Inertial Odometry
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021Visual-inertial odometry (VIO) aims to predict trajectory by ego- motion estimation. In recent years, end-to-end VIO has made great progress. However, how to handle visual and inertial measurements and make full use of the complementarity of cameras and inertial sensors remains a challenge.
Li Liu, Ge Li 0002, Thomas H. Li
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Event-Based Visual Inertial Odometry
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017Event-based cameras provide a new visual sensing model by detecting changes in image intensity asynchronously across all pixels on the camera. By providing these events at extremely high rates (up to 1MHz), they allow for sensing in both high speed and high dynamic range situations where traditional cameras may fail. In this paper, we present the first
Alex Zihao Zhu +2 more
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Edge-based visual-inertial odometry
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017In this paper we propose a method for monocular visual-inertial odometry that utilizes image edges as measurements. In contrast to previous feature-based approaches, the proposed method does not employ any assumption on the geometry of the scene (e.g., it does not assume straight lines).
Hongsheng Yu, Anastasios I. Mourikis
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The First Attempt of SAR Visual-Inertial Odometry
IEEE Transactions on Geoscience and Remote Sensing, 2021This article proposes a novel synthetic aperture radar visual-inertial odometry (SAR-VIO) consisting of an SAR and an inertial measurement unit (IMU), which aims to enable the observation platform to complete successfully a continuous observation mission in the context of low-cost demand and lack of enough navigation information.
Junbin Liu, Xiaolan Qiu, Chibiao Ding
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Information Sparsification in Visual-Inertial Odometry
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018In 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 +4 more
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Compass aided visual-inertial odometry
Journal of Visual Communication and Image Representation, 2019Abstract With the development of vision and optimization techniques, visual-inertial odometry (VIO) has shown the capability of motion estimating in the GNSS-denied condition. The VIO can provide absolute pitch and roll angles estimating value, but no the absolute azimuth. In the paper, we proposed a VIO aided by compass, which can obtain the azimuth
Yandong Wang +5 more
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A Partial Sparsification Scheme for Visual-Inertial Odometry
2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 2020In this paper, we present a partial sparsification scheme for the marginalization of visual inertial odometry (VIO) systems. Sliding window optimization is widely used in VIO systems to guarantee constant complexity by optimizing over a set of recent states and marginalizing out past ones.
Zhikai Zhu, Wei Wang
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