# Limited bene﬿t of cooperation in distributed relative localization

Wilbert Samuel Rossi, Wilbert Samuel Rossi, Paolo Frasca, Fabio Fagnani

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

### Abstract

Important applications in robotic and sensor networks require distributed algorithms to solve the so-called relative localization problem: a node-indexed vector has to be reconstructed from measurements of differences between neighbor nodes. In a recent note, we have studied the estimation error of a popular gradient descent algorithm showing that the mean square error has a minimum at a finite time, after which the performance worsens. This paper proposes a suitable modification of this algorithm incorporating more realistic a priori information on the position. The new algorithm presents a performance monotonically decreasing to the optimal one. Furthermore, we show that the optimal performance is approximated, up to a $1 + \epsilon$ factor, within a time which is independent of the graph and of the number of nodes. This bounded convergence time is closely related to the minimum exhibited by the previous algorithm and both facts lead to the following conclusion: in the presence of noisy data, cooperation is only useful till a certain limit.
Original language Undefined Proceedings of the 52nd IEEE Conference on Decision and Control USA IEEE CONTROL SYSTEMS SOCIETY 5427-5431 5 978-1-4673-5716-6 Published - Dec 2013 52nd IEEE Conference on Decision and Control, CDC 2013 - Florence, ItalyDuration: 10 Dec 2013 → 13 Dec 2013Conference number: 52

### Publication series

Name IEEE Control Systems Society

### Conference

Conference 52nd IEEE Conference on Decision and Control, CDC 2013 CDC Italy Florence 10/12/13 → 13/12/13

### Keywords

• EWI-24173
• IR-88319
• METIS-300255

## Cite this

Rossi, W. S., Rossi, W. S., Frasca, P., & Fagnani, F. (2013). Limited bene﬿t of cooperation in distributed relative localization. In Proceedings of the 52nd IEEE Conference on Decision and Control (pp. 5427-5431). USA: IEEE CONTROL SYSTEMS SOCIETY.