Vision-Based Distributed Formation Control Without an External Positioning System

  title = {Vision-{Based} {Distributed} {Formation} {Control} {Without} an {External} {Positioning} {System}},
  volume = {32},
  issn = {1552-3098, 1941-0468},
  url = {},
  abstract = {In this paper we present a fully distributed solution to drive a team of robots to reach a desired formation in the absence of an external positioning system that localizes them. Our solution addresses two fundamental problems that appear in this context. First, we propose a three dimensional distributed control law, designed at a kinematic level, that uses two simultaneous consensus controllers, one to control the relative orientations between robots, and another for the relative positions. The convergence to the desired configuration is shown by comparing the system with time-varying orientations against the equivalent approach with fixed orientations, showing that their difference vanishes as time goes to infinity. Secondly, in order to apply this controller to a group of aerial robots, we combine this idea with a novel sensor fusion algorithm to estimate the relative pose of the robots using on-board cameras and information from the Inertial Measurement Unit. The algorithm removes the influence of roll and pitch from the camera images, and estimates the relative pose between robots using a structure from motion approach. Simulation results, as well as hardware experiments with a team of three quadrotors, demonstrate the effectiveness of the controller and the vision system working together.},
  language = {en},
  number = {2},
  urldate = {2020-07-21},
  journal = {IEEE Transactions on Robotics},
  author = {Montijano, Eduardo and Cristofalo, Eric and Zhou, Dingjiang and Schwager, Mac and Sagues, Carlos},
  month = apr,
  year = {2016},
  keywords = {formation\_control},
  pages = {339--351},
  month_numeric = {4}