A framework and analysis for cooperative search using UAV swarms
Proceedings of the 2004 ACM symposium on Applied computing
MASON: A Multiagent Simulation Environment
Simulation
Agent-oriented compositional approaches to services-based cross-organizational workflow
Decision Support Systems - Special issue: Web services and process management
On using SPEEDES as a platform for a parallel swarm simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
Service-Oriented Computing and Cloud Computing: Challenges and Opportunities
IEEE Internet Computing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Adaptive Service Workflow Configuration and Agent-Based Virtual Resource Management in the Cloud*
IC2E '13 Proceedings of the 2013 IEEE International Conference on Cloud Engineering
Multi-hop communications in a swarm of UAVs
Proceedings of the Agent-Directed Simulation Symposium
Design and evaluation of UAV swarm command and control strategies
Proceedings of the Agent-Directed Simulation Symposium
Agent-based simulation of cooperative hunting with UAVs
Proceedings of the Agent-Directed Simulation Symposium
Multi-hop communications in a swarm of UAVs
Proceedings of the Agent-Directed Simulation Symposium
Design and evaluation of UAV swarm command and control strategies
Proceedings of the Agent-Directed Simulation Symposium
International Journal of Agent Technologies and Systems
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Swarms of Unmanned Aerial Vehicles (UAV) have been foreseen by multiple organizations to serve an important role in future air-based warfare and civilian operations. UAVs are less expensive than their piloted counterparts, provide greater flexibilities and remove the need for on-board pilot support. Efficient control of swarms opens a set of new challenges, such as automatic UAV coordination, efficient swarm monitoring and dynamic mission planning. In this paper, we investigate the problem of dynamic mission planning for a UAV swarm. An agent-based control framework is proposed, which employs a control agent for task assignment and multiple UAV agents for local task scheduling. A prototype simulation framework is implemented as a proof-of-concept. Experimentation with the framework suggests the effectiveness of swarm control using several mission planning mechanisms.