Results 141 to 150 of about 6,675 (223)
Navigational Drift Analysis for Visual Odometry
Visual odometry estimates a robot's ego-motion with cameras installed on itself. With the advantages brought by camera being a sensor, visual odometry has been widely adopted in robotics and navigation fields.
Hu, Weng +3 more
core
IT-SVO: Improved Semi-Direct Monocular Visual Odometry Combined with JS Divergence in Restricted Mobile Devices. [PDF]
Liu C, Zhao J, Sun N, Yang Q, Wang L.
europepmc +1 more source
RoMeO: Robust Metric Visual Odometry
Visual odometry (VO) aims to estimate camera poses from visual inputs -- a fundamental building block for many applications such as VR/AR and robotics. This work focuses on monocular RGB VO where the input is a monocular RGB video without IMU or 3D sensors.
Junda Cheng +6 more
openaire +2 more sources
Communicationless navigation through robust visual odometry
GPS navigation is often found undependable in urban situations where tall structures occlude large parts of the sky. To keep accurate position in these situations, we need an alternative method.
David Van Hamme +5 more
core +1 more source
Non-Parametric Learning for Monocular Visual Odometry [PDF]
This thesis addresses the problem of incremental localization from visual information, a scenario commonly known as visual odometry. Current visual odometry algorithms are heavily dependent on camera calibration, using a pre-established geometric model ...
Campanholo Guizilini, Vitor
core
SATVIO : Stereo Attention-based Visual Inertial Odometry
This study introduces a novel stereo attention-based visual inertial odometry model, namely, SATVIO, aiming to enhance odometry performance by leveraging deep learning techniques for sensor fusion. The research evaluates the SATVIO model against existing
Doorshi, Raoof +2 more
core +1 more source
Visual Odometry Using Pixel Processor Arrays for Unmanned Aerial Systems in GPS Denied Environments. [PDF]
McConville A +8 more
europepmc +1 more source
Implementation of Visual Odometry on Jetson Nano. [PDF]
Krško J +3 more
europepmc +1 more source
Dense mapping from sparse visual odometry: a lightweight uncertainty-guaranteed depth completion method. [PDF]
Yang D +6 more
europepmc +1 more source

