Globally Exponentially Convergent Continuous Observers for Velocity Bias and State for Invariant Kinematic Systems on Matrix Lie Groups

• Published in: IEEE transactions on automatic control Vol. 66; no. 7; pp. 3363 - 3369
• Main Author: Chang, Dong Eui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-07-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algebra; Bias; Convergence; Estimation; Euclidean geometry; Euclidean space; Invariants; Kinematics; Lie group; Lie groups; Mathematical analysis; Matrix algebra; Noise measurement; observer; Observers; Trajectory; Vectors (mathematics); Velocity; velocity bias; Velocity measurement
• ISSN: 0018-9286; 1558-2523
• DOI: 10.1109/TAC.2020.3022481

In this article globally exponentially convergent continuous observers for invariant kinematic systems on finite-dimensional matrix Lie groups has been proposed. Such an observer estimates, from measurements of landmarks, vectors, and biased velocity, both the system state and the unknown constant bias in velocity measurement, where the state belongs to the state-space Lie group and the velocity to the Lie algebra of the Lie group. The main technique is to embed a given system defined on a matrix Lie group into Euclidean space and build observers in the Euclidean space. The theory is illustrated with the special Euclidean group in three dimensions, and it is shown that the observer works well even in the presence of measurement noise.