Angular Velocity and Linear Acceleration Measurement Bias Estimators for the Rigid Body System With Global Exponential Convergence

ABSTRACT Rigid body systems usually consider measurements of the pose of the body using onboard cameras/LiDAR systems, that of linear acceleration using an accelerometer and of angular velocity using an IMU. However, the measurements of the linear acceleration and angular velocity are usually biased with an unknown constant or slowly varying bias. Estimating this bias is important to recover the true linear acceleration and angular velocity of the system. We propose two measurement bias estimators for such systems under assumption of boundedness of angular velocity. We also provide continuous estimates of the linear velocity of the system. These estimates are globally exponentially convergent to the true state of the rigid body system. The first observer assumes knowledge of bounds of the angular velocity, while the second observer uses a Riccati observer to overcome this limitation. We validate that the observer is able to estimate the bias using numerical simulations and experimental data collected from an Intel Realsense camera.