Automatic synthesis of communication-based coordinated multi-robot systems

To enable the successful deployment of task-achieving multi-robot systems (MRS), coordination mechanisms must be utilized in order to effectively mediate the interactions between the robots and the task environment. Over the past decade, there have been a number of elegant experimentally demonstrated MRS coordination mechanisms. Most of these mechanisms have been task-specific in nature, typically providing only empirical insights into coordination design and little in the way of systematic techniques to assist in the design of coordinated MRS for new task domains. To fully realize the potentials of MRS, formally-grounded systematic techniques amenable to analysis are needed in order to facilitate the design of coordinated MRS. We address this problem by presenting a formal framework for describing and reasoning about coordination in a MRS. Using this principled foundation, we are developing a suite of general methods for automatically synthesizing the controllers of robots constituting a MRS such that the given task is performed in a coordinated fashion. This paper presents a method for the automatic synthesis of a specific type of controller, one that is stateless but capable of inter-robot communication. We also present a graph coloring-based approach for minimizing the number of necessary unique communication messages. The synthesis of such communicative controllers provides a means for assessing the uses and limitations of communication in MRS coordination. We present experimental validation of our formal approach of controller synthesis in a multi-robot construction domain through physically-realistic simulations and in real-robot demonstrations.

[1]  Tucker R. Balch,et al.  Measuring robot group diversity , 2002 .

[2]  Maja J. Mataric,et al.  Synthesis and Analysis of Non-Reactive Controllers for Multi-Robot Sequential Task Domains , 2004, ISER.

[3]  Maja J. Mataric,et al.  Issues and approaches in the design of collective autonomous agents , 1995, Robotics Auton. Syst..

[4]  Francesco Mondada,et al.  Understanding collective aggregation mechanisms: From probabilistic modelling to experiments with real robots , 1999, Robotics Auton. Syst..

[5]  Maja J. Mataric,et al.  Designing and Understanding Adaptive Group Behavior , 1995, Adapt. Behav..

[6]  Michael R. M. Jenkin,et al.  A taxonomy for multi-agent robotics , 1996, Auton. Robots.

[7]  Maja J. Mataric,et al.  Multi-robot task allocation: analyzing the complexity and optimality of key architectures , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[8]  Lynne E. Parker Toward the automated synthesis of cooperative mobile robot teams , 1999, Other Conferences.

[9]  Tucker R. Balch,et al.  AuRA: principles and practice in review , 1997, J. Exp. Theor. Artif. Intell..

[10]  Bruce Randall Donald,et al.  On Information Invariants in Robotics , 1995, Artif. Intell..

[11]  Lynne E. Parker,et al.  ALLIANCE: an architecture for fault tolerant multirobot cooperation , 1998, IEEE Trans. Robotics Autom..

[12]  Vijay Kumar,et al.  Modular Specification of Hybrid Systems in CHARON , 2000, HSCC.

[13]  Kristina Lerman,et al.  Macroscopic analysis of adaptive task allocation in robots , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[14]  Dario Floreano,et al.  Patterns of Interactions in Shared Environments , 1993 .

[15]  Gaurav S. Sukhatme,et al.  Most valuable player: a robot device server for distributed control , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[16]  Andrew Howard,et al.  Design and use paradigms for Gazebo, an open-source multi-robot simulator , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).