Distributed estimation for the unknown orientation of the local reference frames in N-dimensional space
Byung‐Hun Lee, Hyo‐Sung Ahn · 2016
In this paper, we propose a novel distributed orientation estimation method of rigid bodies in n-dimensional space using only relative orientation information. For the orientation estimation, n auxiliary variables for each agent are required. A rotation matrix which identifies orientation of local frame with respect to the common frame is obtained by transforming auxiliary variables with the Gram-Schmidt procedure. Since the auxiliary variables are defined on vector space, a consensus-based control law for auxiliary variables achieves a global convergence. Although there exist initial values of auxiliary variables such that auxiliary variables converge to undesired points, we show that the solution of proposed algorithm can be obtained for almost all initial values.