Nothing Special   »   [go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

Information seeking and model predictive control of a cooperative multi-robot system

  • Special Feature: Original Article
  • Published:
Artificial Life and Robotics Aims and scope Submit manuscript

Abstract

In this paper, we propose a cooperative multi-robot control system, operating in an unfamiliar or unstructured environment. We focus on a robust model predictive control (robust-MPC) framework that enables robotic agents to operate in uncertain environments, and study the effect of observation uncertainties that arise from sensor noise on cooperative control performance. The proposed system relies on cooperative observation based on an information-seeking theory, in which the system not only can compensate uncertainty, but also takes actions to mitigate it. We carry out a case study that demonstrates a multi-robot collision avoidance scenario in an unknown environment. Simulation results show that the combination of robust-MPC methods and cooperative observation enables the cooperative multi-robot system to move efficiently and reach the goal faster than an uncooperative scenario.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Mayne DQ, Seron MM, Rakovic SV (2005) Robust model predictive control of constrained linear systems with bounded disturbances. Automatica 41:219–225

    Article  MathSciNet  MATH  Google Scholar 

  2. Pugh J, Martinoli A (2007) Inspiring and modeling multi-robot search with particle swarm optimization. In: Proceedings of the 4th IEEE Swarm Intelligence Symposium, 332–339

  3. Hofmann GM, Tomlin CJ (2010) Mobile sensor network control using mutual information methods and particle filters. IEEE Trans Autom Control 55(1):32–47

    Article  MathSciNet  Google Scholar 

  4. Charrow B, Kumar V, Michael N (2014) Approximate representations for multi-robot control policies that maximize mutual information. Auton Robots 37(4):383–400

    Article  Google Scholar 

  5. Rasmussen C, Hager GD (2001) Probabilistic data association methods for tracking complex visual objects. IEEE Trans Pattern Anal Mach Intell 23(6):560–576

    Article  Google Scholar 

  6. Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  7. Ptolemaeus C, editor (2014), System design, modeling, and simulation using ptolemy II. Ptolemy.org. http://ptolemy.eecs.berkeley.edu/books/Systems/

  8. Akkaya I, Emoto S, Lee EA (2015), PILOT: An actor-oriented learning and optimization toolkit for robotic swarm applications. In: Second International Workshop on Robotic Sensor Networks (RSN’15), Cyber-Physical Systems Week 2015, 13, April, 2015

Download references

Acknowledgments

This work was supported in part by the Berkeley Ubiquitous SwarmLab and the TerraSwarm Research Center, one of six centers administered by the STARnet phase of the Focus Center Research Program (FCRP), a Semiconductor Research Corporation program sponsored by MARCO and DARPA.

Author information

Authors and Affiliations

  1. IHI Corporation, Yokohama, Japan

    Shuhei Emoto

  2. Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA, USA

    Ilge Akkaya & Edward A. Lee

Authors
  1. Shuhei Emoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ilge Akkaya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Edward A. Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shuhei Emoto.

Additional information

This work was presented in part at the 1st International Symposium on Swarm Behavior and Bio-Inspired Robotics, Kyoto, Japan, October 28–30, 2015.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Emoto, S., Akkaya, I. & Lee, E.A. Information seeking and model predictive control of a cooperative multi-robot system. Artif Life Robotics 21, 393–398 (2016). https://doi.org/10.1007/s10015-016-0315-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10015-016-0315-4

Keywords

Search

Navigation