Improved State Estimation in Quadrotor MAVs: A Novel Drift-Free Velocity Estimator

Abstract

This paper describes the synthesis and evaluation of a novel state estimator for a Quadrotor Micro Aerial Vehicle. Dynamic equations which relate acceleration, attitude and the aero-dynamic propeller drag are encapsulated in an extended Kalman filter framework for estimating the velocity and the attitude of the quadrotor. It is demonstrated that exploiting the relationship between the body frame accelerations and velocities, due to blade flapping, enables drift free estimation of lateral and longitudinal components of body frame translational velocity along with improvements to roll and pitch components of body attitude estimations. Real world data sets gathered using a commercial off-the-shelf quadrotor platform, together with ground truth data from a Vicon system, are used to evaluate the effectiveness of the proposed algorithm.

A nonlinear force observer for quadrotors and application to physical interactive tasks

“…In order to implement (4) one needs the knowledge ofq, q, andq. Measuring or estimating q andq is quite standard in current platforms (see, e.g., [18]). However, for many applications, a reliable measurement of the accelerationq (i.e., both the linear and angular acceleration) is not available.…”

Model-aided state estimation for quadrotor micro air vehicles amidst wind disturbances

“…The validity of this equation for situations where there is no wind has already been analysed in [5]. There, experimental results show that k 1 is approximately a constant, the value of which for a specific quadrotor MAV can be approximated via equation (6) when ground truth state estimates are available.…”

“…In our previous work [5], we have designed and evaluated IMU based, model-aided state estimators for quadrotors. MA-VIF design presented in [1] extended this by incorporating a monocular camera into the state estimator.…”

Fast, on-board, model-aided visual-inertial odometry system for quadrotor micro aerial vehicles

“…They illustrated that in the absence of biases, accelerometer measurements can be low pass filtered to obtain an initial estimate of two components of the quadrotor MAV translational velocity. An attitude and velocity estimator based on this principle was presented by the authors in [5]. However, in this design the accelerometer biases were assumed known and only a partial velocity estimate was available.…”

“…The main characteristic of this dynamic model is the presence of a drag force that is approximately proportional to the projection of MAV body frame velocity v B on to the propeller plane. Here, we present a slightly more accurate form and refer interested reader to [1] and [5] for further information.…”