Controlled Vehicle Exchange and Allocation in Dynamic Teams

Author(s):  
Justin A. Ruths ◽  
Anouck R. Girard ◽  
Joa˜o Borges de Sousa

Here, we present a solution for safe switching amongst dynamic teams of autonomous vehicles. By team, we mean a collection of vehicles that have a common mission, or objective. The design of our solution involves a distributed hierarchical control architecture. It contains five levels that successively abstract the motion of a single vehicle into maneuvers, coordinated maneuvers, tasks and team objectives. We do this in the framework of dynamic networks of hybrid automata and sliding mode control. We establish an information interchange protocol that minimizes bandwidth use and ensures robustness in the switching process, yet allows for communications at all levels of the control architecture. We present results from simulations to demonstrate and implement these ideas.

Author(s):  
Mariam Faied ◽  
Anouck Girard

We address a dynamic configuration strategy for teams of Unmanned Air Vehicles (UAVs). A team is a collection of UAVs which may evolve through different organizations, called configurations. The team configuration may change with time to adapt to changes in the environment. To each configuration there corresponds a set of different properties for the UAVs in the team. The design for the configuration control problem involves a distributed hierarchical control architecture where the properties of the system can be formally analyzed. We do this in the framework of dynamic networks of hybrid automata. We present results from simulation to demonstrate these ideas.


2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Mariam Faied ◽  
Ihemed Assanein ◽  
Anouck Girard

We address a dynamic configuration strategy for teams of Unmanned Air Vehicles (UAVs). A team is a collection of UAVs which may evolve through different organizations, called configurations. The team configuration may change with time to adapt to environmental changes, uncertainty, and adversarial actions. Uncertainty comes from the stochastic nature of the environment and from incomplete knowledge of adversary behaviors. To each configuration, there corresponds a set of different properties for the UAVs in the team. The design for the configuration control problem involves a distributed hierarchical control architecture where the properties of the system can be formally analyzed. We do this in the framework of dynamic networks of hybrid automata. We present results from simulation to demonstrate different scenarios for adversarial response.


2013 ◽  
Vol 462-463 ◽  
pp. 794-797
Author(s):  
Ru Bo Zhang ◽  
Hai Bo Tong ◽  
Chang Ting Shi

This paper present a hybrid, hierarchical control architecture for mission re-planning and plan repair of autonomous underwater vehicle (AUV) navigating in dynamic and uncertain marine environment. The proposal carries out a component-oriented part-based control architecture structured in three parts: situation reasoning, re-planning trigger and hierarchical re-planning layer. Situation reasoning using the unstructured real-word information obtained by sorts of sensor detectes and recognizes uncertain event. According the event types and influence degree, the re-planning trigger decides the re-planning level. Hierarchical re-planning layer contains mission re-planning, task re-planning and behavior re-planning. Different re-planning level depends on the result of re-planning trigger. Preliminary versions of the architecture have been integrated and tested in a marine simulation environment.


2016 ◽  
Vol 16 (4) ◽  
pp. 579-596 ◽  
Author(s):  
Yuquan Leng ◽  
Cen Yu ◽  
Wei Zhang ◽  
Yang Zhang ◽  
Xu He ◽  
...  

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