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 +3 more
doaj +2 more sources
LRPL-VIO: A Lightweight and Robust Visual–Inertial Odometry with Point and Line Features [PDF]
SensorsVisual-inertial odometry (VIO) algorithms, fusing various features such as points and lines, are able to improve their performance in challenging scenes while the running time severely increases.
Feixiang Zheng +4 more
doaj +2 more sources
Visual-Inertial Odometry of Smartphone under Manhattan World
Remote Sensing, 2020 Based on the hypothesis of the Manhattan world, we propose a tightly-coupled monocular visual-inertial odometry (VIO) system that combines structural features with point features and can run on a mobile phone in real-time.
YuAn Wang +3 more
doaj +3 more sources
A Benchmark Comparison of Four Off-the-Shelf Proprietary Visual–Inertial Odometry Systems [PDF]
Sensors, 2022 Hyeong Geun Kim, Pyojin Kim
exaly +2 more sources
CVIWM: A Tightly Coupled State Estimation Method for Poultry House Inspection Robots in Structurally Degraded Environments [PDF]
AnimalsAccurate positioning is essential for inspection robots in caged chicken houses, where long straight corridors, sparse textures, and repetitive structures challenge conventional methods.
Hongfeng Deng +4 more
doaj +2 more sources
An Enhanced Hybrid Visual–Inertial Odometry System for Indoor Mobile Robot [PDF]
Sensors, 2022 Yan-Jie Liu, Liu Yanjie
exaly +2 more sources
An Equivariant Filter for Visual Inertial Odometry [PDF]
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 11 pages, 3 figures, to be published as {van Goor, P., Mahony, R.. (2021). An Equivariant Filter for Visual Inertial Odometry. 2020 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2020.}
Pieter van Goor, Robert E. Mahony
openaire +2 more sources
F-LVINS: Flexible Lidar-Visual-Inertial Odometry Systems
IEEE Access, 2023 The development of a new system called Flexible Lidar-Visual-Inertial Odometry (F-LVINS) offers improved localization accuracy even in challenging environments.
Xiang-Shi Tang, Teng-Hu Cheng
doaj +1 more source
Multi-Sensor Fusion Self-Supervised Deep Odometry and Depth Estimation
Remote Sensing, 2022 This paper presents a new deep visual-inertial odometry and depth estimation framework for improving the accuracy of depth estimation and ego-motion from image sequences and inertial measurement unit (IMU) raw data.
Yingcai Wan +4 more
doaj +1 more source
Visual-Inertial Odometry with Robust Initialization and Online Scale Estimation [PDF]
Sensors, 2018 Jongwoo Lim
exaly +2 more sources