Kalman Filtering on SO(3)
Date:
In virtual/augmented reality applications with an HMD (Head Mounted Displays), it is important to estimate the position and attitude of HMD for proper rendering of virtual objects. In those applications, required precision of estimation is extremely stringent, because even small amount of errors can be instantly observed by the users and make them discomfort. Various sensors cooperate for this estimation problem; the most common types of sensors are vision sensors (RGB/depth camera) and IMU (Inertial Measurement Unit) packages. In this talk, we introduce an attitude tracking algorithm using IMU inspired by classical Kalman filter.