Inertial Velocity and Attitude Estimation for Quadrotors

This work addresses the design and implementation of a filter that estimates the orientation of the body-fixed z axis and the velocity of a quadrotor UAV from the inertial measurement unit (IMU) given a known yaw. The velocity and attitude estimation is possible since the filter employs a linear drag model measuring the drag forces on the quadrotor through the IMU. These forces are functions of the robot's velocity and attitude. In addition, the filter estimates the linear drag parameters and thrust coefficient for the propellers. These parameters may be fed back into a controller to improve tracking performance. Experimental results are used to validate the proposed approach.

I. Introduction

Micro Aerial Vehicles (MAVs)equipped with onboard sensors can help humans in a variety of different applications such as search and rescue [1], manipulation [2], [3], transportation [4], exploration [5], inspection [6], and monitoring [7]. Onboard exteroceptive sensors such as LIDAR [8] and cameras are generally used to estimate the state of the vehicle for navigation purposes. Specifically, cameras are useful sensors to estimate the velocity of the platforms using methods such as optical flow [9] and visual-inertial odometry [10]. However, these sensors may be subject to failure and in many applications it is not possible to use them due to computational and/or payload constraints. Furthermore, certain environments make it challenging or impossible to use them. In these environments, the MAV must rely on other sensors for its odometry, such as an inertial measurement unit (IMU), which contains accelerometers, gyroscopes, and sometimes a magnetometer. IMUs are now available on most quadrotor platforms.