A COMMON CONTROL LANGUAGE FOR DYNAMIC TASKING OF MULTIPLE AUTONOMOUS VEHICLES

Cooperative behavior, visible in many animal species, is achieved through varying degrees of communication (e.g. chemical clues from ants, a bees “dance”). When looking at military operations, groups communicate. In the networking of computers and their coordination, communication is necessary to achieve goals. In the same way, cooperative behavior for autonomous vehicles will require some level of communication between group members. Both military and scientific concepts for autonomous operations are projecting the use of a variety of heterogeneous platforms in groupoperations in order to address various operating regimes and specialized tasks thus introducing unique issues for coordinated operations. We will provide an overview of a Common Control Language (CCL) approach that is a natural extension of a behavior-based control although not limited to such an implementation. In our efforts to define and design a CCL, we are interested in answering the following questions: Can autonomous group control benefit from a specialized control language? Can we capture a language to support agent coordination? Our approach will center on 3 critical requirements that this language must address: 1) a processdescriptive language to be used by the scheduler of a vehicle controller, 2) a vocabulary that can evolve and grow with new applications but is primarily based on a discrete set of fundamental behaviors and 3) a translation scheme for an operator’s mission specifications.

[1]  Andrzej Skowron,et al.  New Directions in Rough Sets, Data Mining, and Granular-Soft Computing , 1999, Lecture Notes in Computer Science.

[2]  Maja J. Matarić,et al.  Robots in Formation Using Local Information , 2002 .

[3]  Katia P. Sycara,et al.  Conversational Case-Based Planning for Agent Team Coordination , 2001, ICCBR.

[4]  Eugene Eberbach,et al.  Expressing evolutionary computation, genetic programming, artificial life, autonomous agents and DNA-based computing in -calculus-revised version , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[5]  Christiane Duarte,et al.  Defining a common control language for multiple autonomous vehicle operation , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[6]  Robin Milner,et al.  Communicating and mobile systems - the Pi-calculus , 1999 .

[7]  Pattie Maes,et al.  Designing autonomous agents: Theory and practice from biology to engineering and back , 1990, Robotics Auton. Syst..

[8]  Barry Brian Werger,et al.  Ayllu: Distributed Port-Arbitrated Behavior-Based Control , 2000 .

[9]  Eugene Eberbach,et al.  A generic tool for distributed AI with matching as message passing , 1997, Proceedings Ninth IEEE International Conference on Tools with Artificial Intelligence.

[10]  Shashi Phoha,et al.  SAMON: communication, cooperation and learning of mobile autonomous robotic agents , 1999, Proceedings 11th International Conference on Tools with Artificial Intelligence.

[11]  Shashi Phoha,et al.  Flexible Optimization and Evolution of Underwater Autonomous Agents , 1999, RSFDGrC.

[12]  Gaurav S. Sukhatme,et al.  An incremental deployment algorithm for mobile robot teams , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Rodney A. Brooks,et al.  Elephants don't play chess , 1990, Robotics Auton. Syst..