Attitude, Linear Velocity and Depth Estimation of a Camera observing a planar target using continuous homography and inertial data

International audienceThis paper revisits the problem of estimating the attitude, linear velocity and depth of an IMU-Camera with respect to a planar target. The considered solution relies on the measurement of the optical flow (extracted from the continuous homography) complemented with gyrometer and accelerometer measurements. The proposed deterministic observer is accompanied with an observability analysis that points out camera's motion excitation conditions whose satisfaction grants stability of the observer and convergence of the estimation errors to zero. The performance of the observer is illustrated by performing experiments on a test-bed IMU-Camera system

Development and evaluation of a dynamically scaled testbed aircraft for a visual inertial odometry dataset

In this thesis we describe the design, manufacturing, and testing of a dynamically scaled aircraft, which is a scaled model of a general aviation vehicle that dynamically behaves in a similar manner as the full-scale aircraft. This scaled model (Cirrus SR22T) is to serve as a testbed for both Distributed Electric Propulsion (DEP) aircraft research and for Visual Inertial Odometry (VIO) research. The aircraft is used as a baseline to compare with the DEP aircraft, to draw conclusion regarding the effect of changing to a DEP configuration, and to provide a way to measure the effect that a DEP configuration would have on a full-scale aircraft. The aircraft is also used to collect data from various onboard sensors to provide a data set for the VIO research community to use

Velocity Aided Attitude Estimation for Aerial Robotic Vehicles Using Latent Rotation Scaling

International audienceFlight performance of aerial robotic vehicles is critically dependent on the quality of the state estimates provided by onboard sensor systems. The attitude estimation problem has been extensively studied over the last ten years and the development of low complexity, high performance, robust non-linear observers for attitude has been one of the enabling technologies fueling the growth of small scale aerial robotic systems. The velocity aided attitude estimation problem, that is simultaneous estimation of attitude and linear velocity of an aerial platform, has only been tackled using the non-linear observer approach in the last few years. Prior contributions have lead to non-linear observers for which either there is no stability analysis or for which the analysis is extremely complex. In this paper, we propose a simple relaxation of the state space, allowing scaled rotation matrices R ∈ R^{3×3} such that RX^\top= uI where X = uR and u > 0 is a positive scalar, along with additional observer dynamics to force u → 1 asymptotically. With this simple augmentation of the observer state space, we propose a non-linear observer with a straightforward Lyapunov stability analysis that demonstrates almost global asymptotic convergence along with local exponential convergence. Simulations as well as experimental results are provided to demonstrate the performance of the proposed observer