Results 31 to 40 of about 6,077 (166)

Improved Point–Line Visual–Inertial Odometry System Using Helmert Variance Component Estimation

Remote Sensing, 2020
Mobile platform visual image sequence inevitably has large areas with various types of weak textures, which affect the acquisition of accurate pose in the subsequent platform moving process. The visual–inertial odometry (VIO) with point features and line
Bo Xu, Yu Chen, Shoujian Zhang, Jingrong Wang   +3 more
doaj   +1 more source

Semi-Direct Point-Line Visual Inertial Odometry for MAVs

Applied Sciences, 2022
Traditional Micro-Aerial Vehicles (MAVs) are usually equipped with a low-cost Inertial Measurement Unit (IMU) and monocular cameras, how to achieve high precision and high reliability navigation under the framework of low computational complexity is the ...
Bo Gao, Baowang Lian, Chengkai Tang
doaj   +1 more source

Deep Learning for Underwater Visual Odometry Estimation

IEEE Access, 2020
This paper addresses Visual Odometry (VO) estimation in challenging underwater scenarios. Robot visual-based navigation faces several additional difficulties in the underwater context, which severely hinder both its robustness and the possibility for ...
Bernardo Teixeira, Hugo Silva, Anibal Matos, Eduardo Silva   +3 more
doaj   +1 more source

Monocular Visual-Inertial Odometry for Agricultural Environments

IEEE Access, 2022
The accuracy of autonomous robot localization using a monocular visual-inertial odometry system (VIO) is significantly reduced in an agricultural environment compared to an urban and indoor environment due to the unstructured scenes with unstable ...
Kaiyu Song, Jingtao Li, Run Qiu, Gaidi Yang   +3 more
doaj   +1 more source

RNGC-VIWO: Robust Neural Gyroscope Calibration Aided Visual-Inertial-Wheel Odometry for Autonomous Vehicle

Remote Sensing, 2023
Accurate and robust localization using multi-modal sensors is crucial for autonomous driving applications. Although wheel encoder measurements can provide additional velocity information for visual-inertial odometry (VIO), the existing visual-inertial ...
Meixia Zhi, Chen Deng, Hongjuan Zhang, Hongqiong Tang, Jiao Wu, Bijun Li   +5 more
doaj   +1 more source

Multisensor Data Fusion for Robust Pose Estimation of a Six-Legged Walking Robot

, 2011
For autonomous navigation tasks it is important that the robot always has a good estimate of its current pose with respect to its starting position and - in terms of orientation - with respect to the gravity vector.
Chilian, Annett, Hirschmüller, Heiko, A. Chilian, H. Hirschmuller, Görner, Martin, M. Gorner   +5 more
core   +1 more source

DeepTIO: A Deep Thermal-Inertial Odometry With Visual Hallucination [PDF]

, 2020
Visual odometry shows excellent performance in a wide range of environments. However, in visually-denied scenarios (e.g. heavy smoke or darkness), pose estimates degrade or even fail.
Markham, A, Wang, W, Wahlstrom, Johan, Saputra, Muhamad Risqi U, Wang, Wei, Lu, CX, Chen, Changhao, Almalioglu, Y, Markham, Andrew, Rosa, Stefano, Lu, Chris Xiaoxuan, Trigoni, N, Saputra, MRU, Trigoni, Niki, de Gusmao, Pedro PB, Wahlstrom, J, Chen, C, Almalioglu, Yasin, de Gusmao, PPB, Rosa, S   +19 more
core   +2 more sources

Improved Multi-Sensor Fusion Dynamic Odometry Based on Neural Networks

Sensors
High-precision simultaneous localization and mapping (SLAM) in dynamic real-world environments plays a crucial role in autonomous robot navigation, self-driving cars, and drone control. To address this dynamic localization issue, in this paper, a dynamic
Lishu Luo, Fulun Peng, Longhui Dong
doaj   +1 more source

Comparison of Three Off-the-Shelf Visual Odometry Systems

Robotics, 2020
Positioning is an essential aspect of robot navigation, and visual odometry an important technique for continuous updating the internal information about robot position, especially indoors without GPS (Global Positioning System). Visual odometry is using
Alexandre Alapetite, Zhongyu Wang, John Paulin Hansen, Marcin Zajączkowski, Mikołaj Patalan   +4 more
doaj   +1 more source

Visual and Visual‐Inertial SLAM Based on Enhanced Deep Learning Features and Motion Smoothness Constraints

Advanced Intelligent Systems, EarlyView.
A visual and visual‐inertial simultaneous localization and mapping (SLAM) algorithm, leveraging enhanced deep learning features and motion smoothness constraints, is proposed in this research work. This method retains the advantages of geometry‐based SLAM methods while effectively utilizing the powerful representational capabilities of data‐driven ...
Maosheng Jiang, Lei Ma, Muhua Zhang, Kai Shen   +3 more
wiley   +1 more source