Decentralized Motion Coordination for a Formation of Rovers

Anjan Kumar Ray, Patrick Benavidez, Laxmidhar Behera, M Jamshidi

    Research output: Contribution to journalArticle

    20 Citations (Scopus)

    Abstract

    Abstract—In this paper, a decentralized formation control isproposed which enables collision free coordination and navigationof agents. We present a simple method to define the formationof multi-agents and individual identities (IDs) of agents. Two decentralizedcoordination and navigation techniques are proposedfor the formation of rovers. Agents decide their own behaviorsonboard depending upon the motion initiative of the master agentof the formation. In these approaches, any agent can estimatebehavior of other agents in the formation. These will reduce thedependency of individual agent on other agents while takingdecisions. These approaches reduce the communication burdenon the formation where only the master agent broadcasts itsmotion status per sampled time. Any front agent can act as amaster agent without affecting the formation in case of fault ininitial master agent. The main idea of this paper is to developan adequate computational model under which agents in theformation will perform to coordinate among each other. Assignmentsof IDs to agents are very useful in real-time applications.These proposed schemes are suitable for obstacle avoidance inunknown environment as a whole formation. Agents are free fromcollision among each other during navigation. These schemes canbe used for velocity as well as orientation alignment problemsfor a multi-agent rover network. These schemes are tested withextensive simulations and responses of agents show satisfactoryperformances to deal with different environmental conditions.
    LanguageEnglish
    Pages369-381
    JournalIEEE Systems Journal
    Volume3
    Issue number3
    DOIs
    Publication statusPublished - Sep 2009

    Fingerprint

    Navigation
    Collision avoidance
    Communication

    Keywords

    • Mobile robot navigation
    • multi-agent formation
    • path planning
    • robotic swarm
    • system of systems.

    Cite this

    Ray, A. K., Benavidez, P., Behera, L., & Jamshidi, M. (2009). Decentralized Motion Coordination for a Formation of Rovers. 3(3), 369-381. https://doi.org/10.1109/JSYST.2009.2031012
    Ray, Anjan Kumar ; Benavidez, Patrick ; Behera, Laxmidhar ; Jamshidi, M. / Decentralized Motion Coordination for a Formation of Rovers. 2009 ; Vol. 3, No. 3. pp. 369-381.
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    abstract = "Abstract—In this paper, a decentralized formation control isproposed which enables collision free coordination and navigationof agents. We present a simple method to define the formationof multi-agents and individual identities (IDs) of agents. Two decentralizedcoordination and navigation techniques are proposedfor the formation of rovers. Agents decide their own behaviorsonboard depending upon the motion initiative of the master agentof the formation. In these approaches, any agent can estimatebehavior of other agents in the formation. These will reduce thedependency of individual agent on other agents while takingdecisions. These approaches reduce the communication burdenon the formation where only the master agent broadcasts itsmotion status per sampled time. Any front agent can act as amaster agent without affecting the formation in case of fault ininitial master agent. The main idea of this paper is to developan adequate computational model under which agents in theformation will perform to coordinate among each other. Assignmentsof IDs to agents are very useful in real-time applications.These proposed schemes are suitable for obstacle avoidance inunknown environment as a whole formation. Agents are free fromcollision among each other during navigation. These schemes canbe used for velocity as well as orientation alignment problemsfor a multi-agent rover network. These schemes are tested withextensive simulations and responses of agents show satisfactoryperformances to deal with different environmental conditions.",
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    author = "Ray, {Anjan Kumar} and Patrick Benavidez and Laxmidhar Behera and M Jamshidi",
    note = "Reference text: [1] J. Y. Tigli and M. C. Thomas, “Use of multi agent systems for mobile robotics control,” in Proc. IEEE Int. Conf. Systems, Man, Cybernetics, San Antonio, TX, Oct. 1994, vol. 1, pp. 588–592. [2] T. Eren, N. Belhumeur, B. D. O. Anderson, and A. S. Morse, “A framwork for maintaining formations based on rigidity,” in Proc. 15th IFAC World Congr. Automatic Control, Barcelona, Spain, Jul. 2002, pp. 2752–2757. [3] S. Carpin and L. Parker, “Cooperative leader following in a distribute multi-robot system,” in Proc. IEEE Int. Conf. Robotics and Automation, 2002, pp. 2994–3001. [4] J. P. Desai, “A graph theoretic approach for modeling mobile robot team formation,” J. Robot. Syst., vol. 19, no. 11, pp. 511–525, 2002. [5] J. Fredslund and M. J. Mataric, “A general algorithm for robot formations using local sensing and minimal communication,” IEEE Trans. Robot. Autom., vol. 18, no. 5, pp. 837–846, Oct. 2002. [6] M. Lemay, F. Michaud, D. L{\'a}tourneau, and J. M. Valin, “Autonomous initialization of robot formations,” in Proc. IEEE Int. Conf. Robotics and Automation (ICRA-2004), 2004, vol. 3, pp. 3018–3023. [7] K. Sugihara and I. Suzuki, “Distributed motion coordination of multiple mobile robots,” in Proc. IEEE Int. Symp. Intelligent Control, Philadelphia, PA, 1990, vol. 1, pp. 138–143. [8] V. Gazi, “Swarm aggregations using artificial potentials and slidingmode control,” IEEE Trans. Robotics, vol. 21, no. 6, pp. 1208–1214, Dec. 2005. [9] T. Nishi, M. Ando, and M. Konishi, “Distributed route planning for multiple mobile robots using an augmented lagrangian decomposition and coordination technique,” IEEE Trans. Robotics, vol. 21, no. 6, pp. 1191–1200, Dec. 2005. [10] S. Svestka and M. H. Overmars, “Coordinated path planning for multiple robots,” Robot Auton. Syst., vol. 23, no. 3, pp. 125–152, 1998. [11] S. Akella and S. Hutchinson, “Coordinating the motions of multiple robots with specified trajectories,” in Proc. IEEE Int. Conf. Robot Autom., 2002, pp. 624–631. [12] M. Dorigo, V. Maniezzo, and A. Colorni, “Ant system: Optimization by a colony of cooperating agents,” IEEE Trans. Syst., Man, Cybern. B; Cybern., vol. 26, no. 1, pp. 1–13, Jan. 1996. [13] R. Zlot, A. Strenz, M. B. Dias, and S. Thayer, “Multi-robot exploration controlled by a market economy,” in Proc. IEEE Int. Conf. Robotics and Automation, 2002, pp. 3016–3023. [14] J. Peng and S. Akella, “Coordinating multiple robots with kynodynamic constraints along specified paths,” Int. J. Robot. Res., vol. 24, no. 4, pp. 295–310, 2005. [15] M. Cao, A. S. Morse, and B. D. O. Anderson, “Coordination of an asynchronous multi-agent system via averaging,” in Proc. 16th IFAC World Congr., Prague, Czech Republic, Jul. 2005. [16] M. M. Zavlanos and G. J. Pappas, “Dynamic assignment in distributed motion planning with local coordination,” IEEE Trans. Robotics, vol. 24, no. 1, pp. 232–242, Feb. 2008. [17] W. Burgard, M. Moors, C. Stachniss, and F. Schneider, “Coordinated multi-robot exploration,” IEEE Trans. Robotics, vol. 21, no. 3, pp. 376–386, Jun. 2005. [18] P. Tabuada, J. Pappas, and P. Lima, “Motion feasibility of multi-agent formations,” IEEE Trans. Robotics, vol. 21, no. 3, pp. 387–392, Jun. 2005. [19] W. Ren and R. W. Beard, “Consensus seeking in multiagent systems under dynamically changing interaction topologies,” IEEE Trans. Autom. Control, vol. 50, no. 5, pp. 655–661, May 2005. [20] W. Ren and Y. Cao, “Simulation and experimental study of consensus algorithms for multiple mobile robots with information feedback,” Intell. Autom. and Soft Comput., vol. 14, no. 1, pp. 73–87, 2008. [21] W. Ren, R. W. Beard, and T. W. McLain, “Coordination variables and consensus building in multiple vehicle systems,” in Cooperative Control, Lecture Notes in Control and Information Sciences. Berlin, Germany: Springer-Verlag, 2005, vol. 309, pp. 171–188. [22] A. K. Ray, L. Behera, and M. Jamshidi, “Sonar-based rover navigation for single or multiple platforms: Forward safe path and target switching approach,” IEEE Syst. J., vol. 2, no. 2, pp. 258–272, Jun. 2008.",
    year = "2009",
    month = "9",
    doi = "10.1109/JSYST.2009.2031012",
    language = "English",
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    pages = "369--381",
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    Ray, AK, Benavidez, P, Behera, L & Jamshidi, M 2009, 'Decentralized Motion Coordination for a Formation of Rovers', vol. 3, no. 3, pp. 369-381. https://doi.org/10.1109/JSYST.2009.2031012

    Decentralized Motion Coordination for a Formation of Rovers. / Ray, Anjan Kumar; Benavidez, Patrick; Behera, Laxmidhar; Jamshidi, M.

    Vol. 3, No. 3, 09.2009, p. 369-381.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Decentralized Motion Coordination for a Formation of Rovers

    AU - Ray, Anjan Kumar

    AU - Benavidez, Patrick

    AU - Behera, Laxmidhar

    AU - Jamshidi, M

    N1 - Reference text: [1] J. Y. Tigli and M. C. Thomas, “Use of multi agent systems for mobile robotics control,” in Proc. IEEE Int. Conf. Systems, Man, Cybernetics, San Antonio, TX, Oct. 1994, vol. 1, pp. 588–592. [2] T. Eren, N. Belhumeur, B. D. O. Anderson, and A. S. Morse, “A framwork for maintaining formations based on rigidity,” in Proc. 15th IFAC World Congr. Automatic Control, Barcelona, Spain, Jul. 2002, pp. 2752–2757. [3] S. Carpin and L. Parker, “Cooperative leader following in a distribute multi-robot system,” in Proc. IEEE Int. Conf. Robotics and Automation, 2002, pp. 2994–3001. [4] J. P. Desai, “A graph theoretic approach for modeling mobile robot team formation,” J. Robot. Syst., vol. 19, no. 11, pp. 511–525, 2002. [5] J. Fredslund and M. J. Mataric, “A general algorithm for robot formations using local sensing and minimal communication,” IEEE Trans. Robot. Autom., vol. 18, no. 5, pp. 837–846, Oct. 2002. [6] M. Lemay, F. Michaud, D. Látourneau, and J. M. Valin, “Autonomous initialization of robot formations,” in Proc. IEEE Int. Conf. Robotics and Automation (ICRA-2004), 2004, vol. 3, pp. 3018–3023. [7] K. Sugihara and I. Suzuki, “Distributed motion coordination of multiple mobile robots,” in Proc. IEEE Int. Symp. Intelligent Control, Philadelphia, PA, 1990, vol. 1, pp. 138–143. [8] V. Gazi, “Swarm aggregations using artificial potentials and slidingmode control,” IEEE Trans. Robotics, vol. 21, no. 6, pp. 1208–1214, Dec. 2005. [9] T. Nishi, M. Ando, and M. Konishi, “Distributed route planning for multiple mobile robots using an augmented lagrangian decomposition and coordination technique,” IEEE Trans. Robotics, vol. 21, no. 6, pp. 1191–1200, Dec. 2005. [10] S. Svestka and M. H. Overmars, “Coordinated path planning for multiple robots,” Robot Auton. Syst., vol. 23, no. 3, pp. 125–152, 1998. [11] S. Akella and S. Hutchinson, “Coordinating the motions of multiple robots with specified trajectories,” in Proc. IEEE Int. Conf. Robot Autom., 2002, pp. 624–631. [12] M. Dorigo, V. Maniezzo, and A. Colorni, “Ant system: Optimization by a colony of cooperating agents,” IEEE Trans. Syst., Man, Cybern. B; Cybern., vol. 26, no. 1, pp. 1–13, Jan. 1996. [13] R. Zlot, A. Strenz, M. B. Dias, and S. Thayer, “Multi-robot exploration controlled by a market economy,” in Proc. IEEE Int. Conf. Robotics and Automation, 2002, pp. 3016–3023. [14] J. Peng and S. Akella, “Coordinating multiple robots with kynodynamic constraints along specified paths,” Int. J. Robot. Res., vol. 24, no. 4, pp. 295–310, 2005. [15] M. Cao, A. S. Morse, and B. D. O. Anderson, “Coordination of an asynchronous multi-agent system via averaging,” in Proc. 16th IFAC World Congr., Prague, Czech Republic, Jul. 2005. [16] M. M. Zavlanos and G. J. Pappas, “Dynamic assignment in distributed motion planning with local coordination,” IEEE Trans. Robotics, vol. 24, no. 1, pp. 232–242, Feb. 2008. [17] W. Burgard, M. Moors, C. Stachniss, and F. Schneider, “Coordinated multi-robot exploration,” IEEE Trans. Robotics, vol. 21, no. 3, pp. 376–386, Jun. 2005. [18] P. Tabuada, J. Pappas, and P. Lima, “Motion feasibility of multi-agent formations,” IEEE Trans. Robotics, vol. 21, no. 3, pp. 387–392, Jun. 2005. [19] W. Ren and R. W. Beard, “Consensus seeking in multiagent systems under dynamically changing interaction topologies,” IEEE Trans. Autom. Control, vol. 50, no. 5, pp. 655–661, May 2005. [20] W. Ren and Y. Cao, “Simulation and experimental study of consensus algorithms for multiple mobile robots with information feedback,” Intell. Autom. and Soft Comput., vol. 14, no. 1, pp. 73–87, 2008. [21] W. Ren, R. W. Beard, and T. W. McLain, “Coordination variables and consensus building in multiple vehicle systems,” in Cooperative Control, Lecture Notes in Control and Information Sciences. Berlin, Germany: Springer-Verlag, 2005, vol. 309, pp. 171–188. [22] A. K. Ray, L. Behera, and M. Jamshidi, “Sonar-based rover navigation for single or multiple platforms: Forward safe path and target switching approach,” IEEE Syst. J., vol. 2, no. 2, pp. 258–272, Jun. 2008.

    PY - 2009/9

    Y1 - 2009/9

    N2 - Abstract—In this paper, a decentralized formation control isproposed which enables collision free coordination and navigationof agents. We present a simple method to define the formationof multi-agents and individual identities (IDs) of agents. Two decentralizedcoordination and navigation techniques are proposedfor the formation of rovers. Agents decide their own behaviorsonboard depending upon the motion initiative of the master agentof the formation. In these approaches, any agent can estimatebehavior of other agents in the formation. These will reduce thedependency of individual agent on other agents while takingdecisions. These approaches reduce the communication burdenon the formation where only the master agent broadcasts itsmotion status per sampled time. Any front agent can act as amaster agent without affecting the formation in case of fault ininitial master agent. The main idea of this paper is to developan adequate computational model under which agents in theformation will perform to coordinate among each other. Assignmentsof IDs to agents are very useful in real-time applications.These proposed schemes are suitable for obstacle avoidance inunknown environment as a whole formation. Agents are free fromcollision among each other during navigation. These schemes canbe used for velocity as well as orientation alignment problemsfor a multi-agent rover network. These schemes are tested withextensive simulations and responses of agents show satisfactoryperformances to deal with different environmental conditions.

    AB - Abstract—In this paper, a decentralized formation control isproposed which enables collision free coordination and navigationof agents. We present a simple method to define the formationof multi-agents and individual identities (IDs) of agents. Two decentralizedcoordination and navigation techniques are proposedfor the formation of rovers. Agents decide their own behaviorsonboard depending upon the motion initiative of the master agentof the formation. In these approaches, any agent can estimatebehavior of other agents in the formation. These will reduce thedependency of individual agent on other agents while takingdecisions. These approaches reduce the communication burdenon the formation where only the master agent broadcasts itsmotion status per sampled time. Any front agent can act as amaster agent without affecting the formation in case of fault ininitial master agent. The main idea of this paper is to developan adequate computational model under which agents in theformation will perform to coordinate among each other. Assignmentsof IDs to agents are very useful in real-time applications.These proposed schemes are suitable for obstacle avoidance inunknown environment as a whole formation. Agents are free fromcollision among each other during navigation. These schemes canbe used for velocity as well as orientation alignment problemsfor a multi-agent rover network. These schemes are tested withextensive simulations and responses of agents show satisfactoryperformances to deal with different environmental conditions.

    KW - Mobile robot navigation

    KW - multi-agent formation

    KW - path planning

    KW - robotic swarm

    KW - system of systems.

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    DO - 10.1109/JSYST.2009.2031012

    M3 - Article

    VL - 3

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    ER -

    Ray AK, Benavidez P, Behera L, Jamshidi M. Decentralized Motion Coordination for a Formation of Rovers. 2009 Sep;3(3):369-381. https://doi.org/10.1109/JSYST.2009.2031012