Formation Control and Network Localization via Distributed Global Orientation Estimation in $3$-D

TL;DR

This paper introduces a distributed formation control method in 3D that estimates global orientations without a shared reference frame, enabling formations to converge exponentially to desired configurations.

Contribution

It presents a novel strategy combining global orientation estimation with formation control, allowing for reliable 3D formation in multi-agent systems without shared references.

Findings

Formation converges globally and exponentially to the desired configuration.

Orientation estimation is achieved through auxiliary variables and rotation matrices.

The method is effective in 3D space with agents lacking a common reference frame.

Abstract

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