Velocity aided attitude estimation for aerial robotic vehicles using latent rotation scaling

Abstract

Flight 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 T = 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.

Supervisory Control of Multirotor Vehicles in Challenging Conditions Using Inertial Measurements

“…Velocity aided attitude estimation combines these two state estimation problems into a single observation problem. The vehicle's linear velocity measurements can be posed in either the inertial frame [36], [37], [38] or in the body fixed frame [39], [40], [41]. Bonnabel [42] proposed an invariant extended Kalman filter (EKF) for velocity and attitude estimation in quaternions.…”

“…developed nonlinear observers based on Lyapunov analysis and approximation arguments [36], [45]. The authors prior work [39], [40] also considers the problem from a nonlinear observer design perspective in the body-fixed frame.…”

Attitude, Linear Velocity and Depth Estimation of a Camera Observing a Planar Target Using Continuous Homography and Inertial Data

“…This led to the development of velocity-aided attitude observers that fuse Inertial Measurement Unit (IMU) readings with the linear velocity measurements [2], [6], [ [12], [15], [18], [22]. The lack of an onboard linear velocity sensor for mini UAVs led other researchers to exploit the vehicle's dynamics equations instead [1], [11], [16], [19].…”

Attitude and gyro bias estimation using GPS and IMU measurements

“…A velocity-aided attitude and gyro bias estimator has been proposed in [8] with global exponential stability by relaxing the attitude estimates to lie outside SO (3). Note that in the above mentioned papers, the IMU measurements are complemented with an inertial frame velocity measurements (such as those obtained from a GPS receiver) where some other existing works have considered linear velocity measurements in the body-fixed frame (such as those obtained from Airspeed or Doppler Velocity Log (DVL) sensors) [9], [10], [11], [12], [13], [14]. This paper addresses the attitude estimation problem using IMU and inertial-frame velocity measurements.…”