Communication decisions in multi-agent cooperation: model and experiments
Proceedings of the fifth international conference on Autonomous agents
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
The giving tree: constructing trees for efficient offline and online multi-robot coverage
Annals of Mathematics and Artificial Intelligence
Multi-UAV Simulator Utilizing X-Plane
Journal of Intelligent and Robotic Systems
Balancing search and target response in cooperative unmanned aerial vehicle (UAV) teams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
RAMS: a fast, low-fidelity, multiple agent discrete-event simulator
Proceedings of the 2013 Summer Computer Simulation Conference
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Sophisticated multi-unmanned aerial vehicle (UAV) simulation environments developed so far intrinsically paid significant attention to high-fidelity flight control system components to realistically account for low-level decision support. However, the use of these simulators often incurs a large overhead when focusing on cooperative high-level decision tasks, such as planning in mobile sensor networks. Therefore, a new discrete-event simulation environment, specially designed to investigate multi-agent search path planning coordination problems for surveillance and reconnaissance is proposed. Named CoUAV, the simulation capability gives the flexibility to define and customize simulation configurations from high-level abstract key components and stochastic events specifically aimed at exploring team coordination strategies for distributed information gathering. It abstracts away costly low-level system specifications. The environment provides the user with problem definition, visualization and post-simulation solution analysis capabilities. The versatility and flexibility of the environment is well-suited to explore the strengths and weaknesses of new and existing coordination strategies through comparative performance analysis over a variety of resource-bounded search path planning problem conditions. As an example, simulation results are presented for a military multi-UAV reconnaissance/target search mission comparing two solution designs.