scholarly journals UAVs Dynamic Mission Management in Adversarial Environments

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Mariam Faied ◽  
Ihemed Assanein ◽  
Anouck Girard
Keyword(s):  
Environmental Changes ◽  
Dynamic Networks ◽  
Hierarchical Control ◽  
Hybrid Automata ◽  
Dynamic Configuration ◽  
Incomplete Knowledge ◽  
Hierarchical Control Architecture ◽  
Mission Management ◽  
Adversarial Environments ◽  
Configuration Control

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.

Hybrid System Modeling for UAV Adversarial Operations

2008 ◽  
Author(s):  
Mariam Faied ◽  
Anouck Girard
Keyword(s):  
Control Problem ◽  
Hybrid System ◽  
System Modeling ◽  
Dynamic Networks ◽  
Hierarchical Control ◽  
Control Architecture ◽  
Hybrid Automata ◽  
Dynamic Configuration ◽  
Hierarchical Control Architecture ◽  
Configuration Control

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.

Controlled Vehicle Exchange and Allocation in Dynamic Teams

2005 ◽  
Author(s):  
Justin A. Ruths ◽  
Anouck R. Girard ◽  
Joa˜o Borges de Sousa
Keyword(s):  
Autonomous Vehicles ◽  
Sliding Mode ◽  
Dynamic Networks ◽  
Hierarchical Control ◽  
Control Architecture ◽  
Hybrid Automata ◽  
Hierarchical Control Architecture ◽  
Single Vehicle ◽  
Dynamic Teams ◽  
Information Interchange

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.

A Control Architecture for Mission Re-Planning and Plan Repair of AUV

2013 ◽  
Vol 462-463 ◽  
pp. 794-797
Author(s):  
Ru Bo Zhang ◽  
Hai Bo Tong ◽  
Chang Ting Shi
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Hierarchical Control ◽  
Underwater Vehicle ◽  
Control Architecture ◽  
Real Word ◽  
Simulation Environment ◽  
Hierarchical Control Architecture ◽  
Planning Task ◽  
And Behavior ◽  
Influence Degree

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.

Task-oriented hierarchical control architecture for swarm robotic system

2016 ◽  
Vol 16 (4) ◽  
pp. 579-596 ◽  
Author(s):  
Yuquan Leng ◽  
Cen Yu ◽  
Wei Zhang ◽  
Yang Zhang ◽  
Xu He ◽  
...  
Keyword(s):  
Hierarchical Control ◽  
Robotic System ◽  
Control Architecture ◽  
Hierarchical Control Architecture ◽  
Task Oriented

GAIT GENERATION AND OPTIMIZATION USING THE ESTIMATION OF DISTRIBUTION ALGORITHM FOR TEENSIZE HUMANOID SOCCER ROBOT RESr-1

2008 ◽  
Vol 05 (03) ◽  
pp. 437-456 ◽  
Author(s):  
LINGYUN HU ◽  
CHANGJIU ZHOU
Keyword(s):  
Hierarchical Control ◽  
Estimation Of Distribution Algorithm ◽  
Human Robot Interaction ◽  
Cooperative Research ◽  
Soccer Robot ◽  
Robot Interaction ◽  
Planning And Control ◽  
Hierarchical Control Architecture ◽  
Estimation Of Distribution ◽  
And Control

This paper gives an overview of locomotion planning and control of a TeenSize humanoid soccer robot, Robo-Erectus Senior (RESr-1), which has been developed as an experimental platform for human–robot interaction and cooperative research in general and robotics soccer games in particular. The locomotion planning and control, along with an introduction of hierarchical control architecture, vision-based behavior and its application in the Humanoid TeenSize soccer challenge, are elaborated. The Estimation of Distribution Algorithm (EDA) is used in locomotion generation and optimization to achieves dynamically stable walk and a powerful kick. By setting different objective functions, smooth walking and powerful kicking can be generated quickly. RESr-1 made its debut at RoboCup 2007, and got fourth place in the Humanoid TeenSize penalty kick competition. In addition, some experimental results on RESr-1's walking, tracking and kicking are presented.

Whole-Body Balancing Walk Controller for Position Controlled Humanoid Robots

2016 ◽  
Vol 13 (01) ◽  
pp. 1650011 ◽  
Author(s):  
Seung-Joon Yi ◽  
Byoung-Tak Zhang ◽  
Dennis Hong ◽  
Daniel D. Lee
Keyword(s):  
Hierarchical Control ◽  
Humanoid Robots ◽  
Whole Body ◽  
Appropriate Behavior ◽  
Low Level ◽  
Push Recovery ◽  
Hierarchical Control Architecture ◽  
High Level ◽  
Experimental Trials ◽  
Decision Boundaries

Bipedal humanoid robots are intrinsically unstable against unforeseen perturbations. Conventional zero moment point (ZMP)-based locomotion algorithms can reject perturbations by incorporating sensory feedback, but they are less effective than the dynamic full body behaviors humans exhibit when pushed. Recently, a number of biomechanically motivated push recovery behaviors have been proposed that can handle larger perturbations. However, these methods are based upon simplified and transparent dynamics of the robot, which makes it suboptimal to implement on common humanoid robots with local position-based controllers. To address this issue, we propose a hierarchical control architecture. Three low-level push recovery controllers are implemented for position controlled humanoid robots that replicate human recovery behaviors. These low-level controllers are integrated with a ZMP-based walk controller that is capable of generating reactive step motions. The high-level controller constructs empirical decision boundaries to choose the appropriate behavior based upon trajectory information gathered during experimental trials. Our approach is evaluated in physically realistic simulations and on a commercially available small humanoid robot.

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