Coordination Challenges and Issues in Stability, Security, Transition and Reconstruction and Cooperative Unmanned Aerial Vehicle Scenarios

Abstract : Through the emergence of new doctrine stability operations are becoming a core U.S. military mission that the Department of Defense (DoD) must be prepared to conduct and support. These operations are now given priority comparable to combat operations. The immediate goal often is to provide the local populace with security, restore essential services, and meet humanitarian needs. The long-term goal is to help develop indigenous capacity for securing and providing essential services. Many stability operations tasks are best performed by indigenous, foreign or U.S. civilian professionals. Large scale disasters are an example where Stability, Security Transition and Reconstruction (SSTR) operations can provide value to foreign governments and nongovernmental institutions which are under great stress to respond in a timely and effective manner. Without the means to properly coordinate these efforts, basic assistance and relief operations would be severely impeded. The use of Unmanned Aerial Vehicles (UAVs) to support Intelligence, Surveillance and Reconnaissance (ISR) is becoming increasingly important. These assets can enable the collection of needed information for the execution of a given set of tasks. In large scale operations however, the ability for the UAVs to self-coordinate may be needed as it will be difficult for human operators to effectively control large teams of UAVs. This paper will begin by introducing some of the key aspects of multiagent coordination, with a focus on the operational challenges with regard to SSTR such as disaster management response as well as UAV coordination. We will then discuss the coordination challenges and gaps in order to motivate an adaptive multiagent based approach to coordination as well as additional opportunities for research. We will conclude with a brief summary.

[1]  Michael J. Shaw,et al.  A multi-agent framework for the coordination and integration of information systems , 1998 .

[2]  Robert Tolksdorf,et al.  Models of Coordination , 2000, ESAW.

[3]  Henry Mintzberg,et al.  The structuring of organizations : a synthesis of the research , 1980 .

[4]  Makoto Yokoo,et al.  Distributed Constraint Satisfaction , 2000, Springer Series on Agent Technology.

[5]  Kevin Crowston,et al.  What is coordination theory and how can it help design cooperative work systems? , 1990, CSCW '90.

[6]  Nikos Vlassis,et al.  A Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence I Mobk077-fm Synthesis Lectures on Artificial Intelligence and Machine Learning a Concise Introduction to Multiagent Systems and Distributed Artificial Intelligence a Concise Introduction to Multiagent Systems and D , 2007 .

[7]  Edmund H. Durfee,et al.  Scaling Up Agent Coordination Strategies , 2001, Computer.

[8]  Ranjeev Mittu,et al.  Design and Evaluation of Distributed Role Allocation Algorithms in Open Environments , 2005, IC-AI.

[9]  Gerhard Weiss,et al.  Multiagent systems: a modern approach to distributed artificial intelligence , 1999 .

[10]  Sarit Kraus,et al.  Adaptive Robotic Communication using Coordination Costs for Improved Trajectory Planning , 2006, AAAI Spring Symposium: Distributed Plan and Schedule Management.

[11]  T. J. Grant,et al.  Agent Coordination Mechanisms for Multi-National Network Enabled Capabilities , 2006 .

[12]  Wei-Min Shen,et al.  Distributed constraint optimization for multiagent systems , 2003 .

[13]  Leonid Sheremetov,et al.  Weiss, Gerhard. Multiagent Systems a Modern Approach to Distributed Artificial Intelligence , 2009 .