Observer design for visual inertial SLAM scale on a quadrotor UAV

Estimation of an Unmanned Aerial Vehicle's (UAV) state, i.e., its pose and velocity, is fundamentally important to its operation. Computer vision provides an alternate or augmentation source for performing state estimation. This work uses an existing monocular Visual Simultaneous Localization and Mapping (VSLAM) system which estimates scaled vehicle position. Two observers are proposed for Visual Inertial Simultaneous Localization and Mapping (VISLAM) by combining measurements from an Inertial Measurement Unit (IMU) with the VSLAM system output to estimate vehicle position, linear velocity, and accelerometer bias. Attitude is assumed measured from an onboard Attitude Heading and Reference System (AHRS). We introduce a change of coordinates to transform the system into a Linear Time-Varying (LTV) form. Using these coordinates we study the observability of the VISLAM problem and present two observer designs. The approach does not require an approximate linearization of the model equations. Simulations and experimental results onboard a quadrotor UAV validate the proposed designs.