Drift-free attitude estimation for accelerated rigid bodies

Abstract

In this paper we study the attitude estimation problem for an accelerated rigid body using gyros and accelerometers. The application in mind is that of a walking robot and particular attention is paid to the large and abrupt changes in accelerations that can be expected in such an environment. We propose a state estimation algorithm that fuses data from rate gyros and accelerometers to give long-term drift free attitude estimates. The algorithm does not use any local parameterization of the rigid body kinematics and can thus be used for a rigid body performing any kind of rotations. The algorithm is a combination of two non-standard, but in a sense linear, Kalman ÿlters between which a trigger based switching takes place. The kinematics representation used makes it possible to construct a linear algorithm that can be shown to give convergent estimates for this nonlinear problem. The state estimator is evaluated in simulations demonstrating how the estimates are long-term stable even in the presence of gyro drift. ?

Open Solution for Humanoid Attitude Estimation through Sensory Integration and Extended Kalman Filtering

“…Even if the attitude estimation is a classical problem in mobile wheeled robotics [5], [6] and unmanned aerial vehicles (UAV) [7], [8], [9], several researchers have extended Open Solution for Humanoid Attitude Estimation P. Pierro, C. A. Monje, N. Mansard, P. Souères, C. Balaguer such techniques to legged locomotion [10], [11], [12], [13], [14].…”

“…For instance, Rehbinder and Hu have previously designed an algorithm [18] for fusing inclinometer and gyro data assuming low translational accelerations, which may not be very realistic for a walking robot. Successively, they have provided an algorithm consisting of two modes: one when accelerations are low and the other when these are high [13]. More recent works are [19], [20], where the approach is the use of extended Kalman filters for three-dimensional pose estimation.…”

Global optimal attitude estimation using uncertainty ellipsoids

“…The following result, proved in [1], gives an unique estimate C ∈ SO(3) of the attitude matrix that satisfies (2) and solves the attitude determination problem (1).…”

“…The attitude is represented globally using proper orthogonal matrices and the exponential map on the set of 3 × 3 skew-symmetric matrices. Such a global representation has been recently used for partial attitude estimation with a linear dynamics model in [2]. The estimation scheme presented here is deterministic, based on known measurement uncertainty bounds propagated by the dynamic flow.…”

“…A sample of the literature in spacecraft attitude estimation can be found in [4][5][6][7][8]. Applications of attitude estimation to unmanned vehicles and robots can be found in [2,[9][10][11]. Most existing attitude estimation schemes use generalized coordinate representations of the attitude.…”