Results 51 to 60 of about 23,972 (233)
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 +1 more source
ESVO2: Direct Visual-Inertial Odometry With Stereo Event Cameras [PDF]
IEEE Transactions on roboticsEvent-based visual odometry is a specific branch of visual simultaneous localization and mapping (SLAM) techniques, which aims at solving tracking and mapping subproblems (typically in parallel), by exploiting the special working principles of ...
Junkai Niu +5 more
semanticscholar +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 +3 more
doaj +1 more source
A Tutorial on Quantitative Trajectory Evaluation for Visual(-Inertial) Odometry
IEEE/RJS International Conference on Intelligent RObots and Systems, 2018 In this tutorial, we provide principled methods to quantitatively evaluate the quality of an estimated trajectory from visual(-inertial) odometry (VO/VIO), which is the foundation of benchmarking the accuracy of different algorithms.
Zichao Zhang, D. Scaramuzza
semanticscholar +1 more source
Selective Sensor Fusion for Neural Visual-Inertial Odometry [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Deep learning approaches for Visual-Inertial Odometry (VIO) have proven successful, but they rarely focus on incorporating robust fusion strategies for dealing with imperfect input sensory data. We propose a novel end-to-end selective sensor fusion framework for monocular VIO, which fuses monocular images and inertial measurements in order to estimate ...
Chen, C +6 more
openaire +3 more sources
Improved Multi-Sensor Fusion Dynamic Odometry Based on Neural Networks
SensorsHigh-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
Ultra-Wideband Aided Fast Localization and Mapping System
, 2017 This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces ...
Nguyen, Thien-Minh +3 more
core +1 more source
Direct visual-inertial odometry with semi-dense mapping [PDF]
Computers & Electrical Engineering, 2018 The paper presents a direct visual-inertial odometry system. In particular, a tightly coupled nonlinear optimization based method is proposed by integrating the recent advances in direct dense tracking and Inertial Measurement Unit (IMU) pre-integration, and a factor graph optimization is adapted to estimate the pose of the camera and rebuild a semi ...
Wenju Xu, Dongkyu Choi, Guanghui Wang
openaire +2 more sources
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 +4 more
doaj +1 more source
Attention and Anticipation in Fast Visual-Inertial Navigation [PDF]
, 2018 We study a Visual-Inertial Navigation (VIN) problem in which a robot needs to estimate its state using an on-board camera and an inertial sensor, without any prior knowledge of the external environment.
Carlone, Luca, Karaman, Sertac
core +2 more sources