Pose Localization of Leader-Follower Networks with Direction Measurements

TL;DR

This paper introduces a distributed pose localization method for leader-follower multi-agent systems in 3D that relies solely on direction measurements, eliminating the need for distance or relative orientation data.

Contribution

The novel localization approach uses only directional constraints and angular velocities, enabling simultaneous pose estimation without distance measurements.

Findings

Achieves almost global asymptotic convergence in stationary scenarios.

Provides a distributed algorithm based on differential equations.

Effectively tracks time-varying orientations.

Abstract

A distributed pose localization framework based on direction measurements is proposed for a type of \textit{leader-follower} multi-agent systems in $\mathbb{R}^3$. The novelty of the proposed localization method lies in the elimination of the need for using distance measurements and relative orientation measurements for the network pose localization problem. In particular, a network localization scheme is developed based directly on the measured direction constraints between an agent and its neighboring agents in the network. The proposed position and orientation localization algorithms are implemented through differential equations which simultaneously compute poses of all followers by using locally measured directional vectors and angular velocities, and actual pose knowledge of some leader agents, allowing some tracking of time-varying orientations. Further, we establish an almost global asymptotic convergence of the estimated positions and orientations of the agents to the actual poses in the stationary case.