VIO-DualProNet: Visual-Inertial Odometry with Learning Based Process Noise Covariance

Understand

Visual-inertial odometry (VIO) is a vital technique used in robotics, augmented reality, and autonomous vehicles.

• It combines visual and inertial measurements to accurately estimate position and orientation.
• Existing VIO methods assume a fixed noise covariance for the inertial uncertainty.
• However, accurately determining in real-time the noise variance of the inertial sensors presents a significant challenge as the uncertainty changes throughout the operation leading to suboptimal performance and reduced accuracy.