RaD-VIO: Rangefinder-aided Downward Visual-Inertial Odometry

10/19/2018
by   Bo Fu, et al.
0

State-of-the-art forward facing monocular visual-inertial odometry algorithms are often brittle in practice, especially whilst dealing with initialisation and motion in directions that render the state unobservable. In such cases having a reliable complementary odometry algorithm enables robust and resilient flight. Using the common local planarity assumption, we present a fast, dense, and direct frame-to-frame visual-inertial odometry algorithm for downward facing cameras that minimises a joint cost function involving a homography based photometric cost and an IMU regularisation term. Via extensive evaluation in a variety of scenarios we demonstrate superior performance than existing state-of-the-art downward facing odometry algorithms for Micro Aerial Vehicles (MAVs).

READ FULL TEXT

page 4

page 5

research
06/07/2019

Visual-Inertial Odometry of Aerial Robots

Visual-Inertial odometry (VIO) is the process of estimating the state (p...
research
11/30/2017

Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight

In recent years, vision-aided inertial odometry for state estimation has...
research
10/16/2018

StructVIO : Visual-inertial Odometry with Structural Regularity of Man-made Environments

We propose a novel visual-inertial odometry approach that adopts structu...
research
09/02/2021

MIR-VIO: Mutual Information Residual-based Visual Inertial Odometry with UWB Fusion for Robust Localization

For many years, there has been an impressive progress on visual odometry...
research
11/23/2021

RIO: Rotation-equivariance supervised learning of robust inertial odometry

This paper introduces rotation-equivariance as a self-supervisor to trai...
research
01/24/2021

VIO-Aided Structure from Motion Under Challenging Environments

In this paper, we present a robust and efficient Structure from Motion p...
research
08/30/2022

CUAHN-VIO: Content-and-Uncertainty-Aware Homography Network for Visual-Inertial Odometry

Learning-based visual ego-motion estimation is promising yet not ready f...

Please sign up or login with your details

Forgot password? Click here to reset