Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Systems and Control pp 1–8Cite as

Image-Based Formation Control of Mobile Robots

  • Living reference work entry
  • First Online:

  • 209 Accesses

Abstract

This chapter addresses an image-based cooperative formation control problem of multiple mobile robots. To develop the image-based feedback controller, the homography matrix or essential matrix techniques are employed to achieve geometric relationships that are beneficial to image-based formation control. Then, image-based cooperative state estimation and cooperative formation control designs are considered, respectively. Finally, a short discussion section is provided to summarize existing research and to point out several future research directions.

This is a preview of subscription content, log in via an institution.

Bibliography

  • Carli R, Chiuso A, Schenato L, Zampieri S (2008) Distributed Kalman filtering based on consensus strategies. IEEE J Sel Areas Commun 26(4):622–633

    Article  Google Scholar 

  • Cook J, Hu G (2012) Vision-based triangular formation control of mobile robots. In: Chinese control conference, Hefei, pp 5146–5151

    Google Scholar 

  • Cook J, Hu G, Feng Z (2012) Cooperative state estimation in vision-based robot formation control via a consensus method. In: Chinese control conference, Hefei, pp 6461–6466

    Google Scholar 

  • Balch T, Arkin R (1998) Behavior-based formation control for multi-robot systems. IEEE Trans Robot Autom 14(6):926–939

    Article  Google Scholar 

  • Das AK, Fierro R, Kumar V, Ostrowski JP, Spletzer J, Taylor CJ (2002) A vision-based formation control framework. IEEE Trans Robot Autom 18(5): 813–825

    Article  Google Scholar 

  • Diestel R (2000) Graph theory. Springer, New York

    MATH  Google Scholar 

  • Egerstedt M, Hu X (2001) Formation constrained multi-agent control. IEEE Trans Robot Autom 17(6): 947–951

    Article  Google Scholar 

  • Kwon C, Hwang I (2019) Sensing-based distributed state estimation for cooperative multiagent systems. IEEE Trans Autom Control 64(6):2368–2382

    Article  MathSciNet  Google Scholar 

  • Mariottini GL, Morbidi F, Prattichizzo D, Valk NV, Michael N, Pappas G, Daniilidis K (2009) Vision-based localization for leader–follower formation control. IEEE Trans Robot 25(6):1431–1438

    Article  Google Scholar 

  • Mateos G, Giannakis GB (2012) Distributed recursive least squares: stability and performance analysis. IEEE Trans Sig Process 60(7):3740–3754

    Article  MathSciNet  Google Scholar 

  • Morbidi F, Bullo F, Prattichizzo D (2011) Visibility maintenance via controlled invariance for leader-follower vehicle formations. Automatica 47(5):1060–1067

    Article  MathSciNet  Google Scholar 

  • Moshtagh N, Michael N, Jadbabaie A, Daniilidis K (2009) Vision-based, distributed control laws for motion coordination of nonholonomic robots. IEEE Trans Robot 25(4):851–860

    Article  Google Scholar 

  • Nedic A, Olshevsky A, Uribe CA (2017) Fast convergence rates for distributed non-Bayesian learning. IEEE Trans Autom Control 62(11):5538–5553

    Article  MathSciNet  Google Scholar 

  • Paley RSD, Leonard NE (2007) Stabilization of planar collective motion: all-to-all communication. IEEE Trans Autom Control 52(5):811–824

    Article  MathSciNet  Google Scholar 

  • Panagou D, Kumar V (2009) Cooperative visibility maintenance for leader-follower formations in obstacle environments. IEEE Trans Robot 30(4):831–834

    Article  Google Scholar 

  • Ren W (2010) Consensus tracking under directed interaction topologies: algorithms and experiments. IEEE Trans Control Syst Technol 18(1):230–237

    Article  Google Scholar 

  • Sun D, Wang C, Shang W, Feng G (2009) A synchronization approach to trajectory tracking of multiple mobile robots while maintaining time-varying formations. IEEE Trans Robot 25(5):1074–1086

    Article  Google Scholar 

  • Tu S, Sayed A (2012) Diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks. IEEE Trans Sig Process 60(12):6217–6234

    Article  MathSciNet  Google Scholar 

  • Vidal R, Shakernia O, Sastry S (2004) Following the flock: distributed formation control with omnidirectional vision-based motion segmentation and visual servoing. IEEE Robot Autom Mag 11(4):14–20

    Article  Google Scholar 

  • Wang S, Ren W, Chen J (2017) Fully distributed dynamic state estimation with uncertain process models. IEEE Trans Control Netw Syst 5(4):1841–1851

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Guoqiang Hu, Zhi Feng & Renhe Guan

Authors
  1. Guoqiang Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhi Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Renhe Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Electrical and Computer Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Automation and Control Solutions, Honeywell, Golden Valley, MN, USA

    Tariq Samad

Section Editor information

  1. Dept. of Mechanical and AeroMechanical and Aerospace Engineering, University of Florida, Room 334, MAE-B, Gainesville, FL, USA

    Warren Dixon

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer-Verlag London Ltd., part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Hu, G., Feng, Z., Guan, R. (2020). Image-Based Formation Control of Mobile Robots. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, London. https://doi.org/10.1007/978-1-4471-5102-9_100152-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4471-5102-9_100152-1

  • Published:

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5102-9

  • Online ISBN: 978-1-4471-5102-9

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation