Distributed Orientation Estimation in SO(d) and applications to formation control and network localization

Abstract

In this paper, we propose a novel distributed orientation estimation strategy, which is based on the measurements of relative orientations of neighbors, in d-dimensional space, where d ≥q 3. Since agents do not share a common reference frame, local reference frames are not aligned with each other. Under the proposed orientation estimation law, a rotation matrix that identifies the orientation of a local frame with respect to a common frame is obtained by auxiliary variables. The proposed estimation strategy is applied to formation control and network localization in 3-D space. Since the orientation of each agent is estimated in a global sense, formation control strategy ensures that the formation globally exponentially converges to the desired formation in 3-D space. © 2014 IEEE.