Anouck R. Girard

Border patrol and surveillance missions using multiple unmanned air vehicles

In this paper, we propose hierarchical control architecture for a system that does border or perimeter patrol using unmanned air vehicles (AUV). By control architecture we mean a specific way of organizing the motion control and navigation functions performed by the UAV. It is convenient to organize the functions into hierarchical layers. This way, a complex design problem is partitioned into a number of more manageable subproblems that are addressed in separate layers. This paper discusses vehicle control requirements and maps them onto layered control architecture. The formalization of the hierarchy is accomplished in terms of the specific functions accomplished by each layer and of the interfaces between layers. The implementation of the layers is discussed and illustrative examples are provided.

A control architecture for integrated cooperative cruise control and collision warning systems

In this paper, we propose a hierarchical control architecture for an enhanced variant of Cooperative Adaptive Cruise Control (CACC), which would include some Cooperative Forward Collision Warning (CFCW) functionality. Simply put, a CACC system is a more sophisticated variant of cruise control. By a control architecture we mean a specific way of organizing the motion control and navigation functions performed by the cars. It is convenient to organize the functions into hierarchical layers. This way, a complex design problem is partitioned into a number of more manageable sub-problems that are addressed in separate layers. This paper discusses vehicle control requirements and maps them onto a layered control architecture. The formalization of the hierarchy is accomplished in terms of the specific functions accomplished by each layer and of the interfaces between layers. The implementation of the layers is discussed and illustrative examples are provided.

Modeling and Simulation of Nonlinear Dynamics of Flapping Wing Micro Air Vehicles

included. Simulations are compared with previous modeling efforts, which neglected the wings’ mass and the associated inertial coupling effects on the body. Simulations show a qualitative consistency for the nonlinear model with wing effects when different aerodynamic models are chosen as inputs. Simulation results show a significant differenceinthemodelbehaviorwhenthemassofthewings,initiallysetat5.7%ofthebodymass,isincludedversus whenthemassisneglected.Asthemassofthewingsisdecreased,thesimulationresultsofthemodelwithwingeffects approachtheresultswhenthestandardaircraftmodelisused.Simulationsleadtotheconclusionthatthemasseffects of the wings are important for dynamics, stability, and control analyses.

Autonomous battery swapping system for small-scale helicopters

A large focus of the Unmanned Aerial Vehicle (UAV) community has been shifted to addressing the requirements necessary for managing systems of UAVs. The ability to automate the process of tracking and responding to the health of UAVs contributes to the reliable and persistent operation of multiple UAV systems. In particular, the automation of managing UAVs and their resources removes a critical, frequent, and time consuming task from an operators workload. We have developed a battery swapping mechanism capable of ‘refueling’ UAVs autonomously. This paper presents an automated battery swapping system for multiple small-scale UAVs. The system includes a battery swapping mechanism and online algorithms to address resource management, vehicle health monitoring, and precision landing onto the battery swapping mechanisms landing platform.

On Codiagnosability and Coobservability With Dynamic Observations

Codiagnosability and coobservability in discrete event systems where observations are dynamic are considered. Instead of having a fixed set of observable events, the observation of an event is dynamic (trace-dependent) in this paper. A procedure is developed to transform the problem of coobservability to the problem of codiagnosability in the context of dynamic observations. This proves that problems of coobservability are transformable to problems of codiagnosability and enables us to leverage the large literature available for codiagnosability to solve problems of coobservability. Furthermore, in the case of dynamic observations, the known polynomial-complexity tests for the property of codiagnosability based on verifier automata with fixed observable event set(s) are no longer directly applicable. A new testing procedure is developed that can handle transition-based dynamic observations and remains of polynomial complexity in the state space of the system. This new testing procedure employs a covering of the state space of the system based on cluster automata, which enhances its computational efficiency. Based on cluster automata, a new type of verifier automaton is built, called the C-VERIFIER, for verification of codiagnosability. As an application of the above mentioned transformation, the C-VERIFIER becomes a unified method for verifying both codiagnosability and coobservability.

Path planning for cooperative time-optimal information collection

Motivated by cooperative exploration missions, this paper considers constant velocity, level flight path planning for Unmanned Air Vehicles (UAVs) equipped with range limited, omni-directional sensors. These active energy-based sensors collect information about objects of interest at rates that depend on the range to the objects according to Shannons channel capacity equation, where the signal-to-noise ratio is governed by the radar equation. The mission of the UAVs is to travel through a given area and collect a specified amount of information about each object of interest while minimizing the total mission time. This information can then be used to classify the objects of interest. An optimal path planning problem is formulated where the states are the Cartesian coordinates of the UAVs and the amounts of information collected about each object of interest, the control inputs are the UAV heading angles, the objective function is the total mission time, and the boundary conditions are subject to inequality constraints that reflect the requirements of information collection. Necessary conditions for optimality are given, whose solutions yield extremal paths, and whose utilization highlights analytical properties of these extremal paths. The problem exhibits several limiting regimes, including the so-called Watchtower and the Multi-Vehicle Traveling Salesman Problem. These results are illustrated on several time-optimal cooperative exploration scenarios.

Convoy protection using multiple unmanned aerial vehicles: organization and coordination

This paper addresses the problem of how to use a given set of possibly heterogeneous unmanned aerial vehicles (UAVs) to provide protection to a moving convoy of ground vehicles. By protection, we mean providing video or sensor coverage of a moving region around the convoy. A hierarchical system design is described that addresses how convoy protection missions may be organized and how those missions might fit into a larger context. The system encompasses task generation and allocation, flight path generation and tracking, and synchronization between cooperative tasks. Task allocation is posed as a constraint satisfaction problem. The design of two classes of orbital flight paths, lateral and longitudinal, is discussed. A coordination algorithm is described that allows the aircraft to synchronize their motions to provide improved sensor coverage. Results of a hardware-in-the-loop simulation are shown.

Wind-field reconstruction using flight data

Although guidance of all aircraft is affected by wind disturbances, micro-UAVs are especially susceptible. To estimate unknown wind disturbance, we consider two illustrative scenarios for planar flight. In the first scenario, we assume that measurements of the heading angle are available, while, in the second scenario, we assume that measurements of the heading angle are not available. Since the disturbance estimation problem is nonlinear, we develop an extension of the unscented Kalman filter that provides an estimate of the unknown wind disturbance. Furthermore, we show through simulations that, when the heading angle is not measured, a kinematic ambiguity is introduced. However, when the initial heading angle is known and the subsequent heading angle is not measured, this kinematic ambiguity is resolved and accurate estimates of the wind velocity are obtained.

Minimization of Dynamic Sensor Activation in Discrete Event Systems for the Purpose of Control

This paper considers centralized and decentralized control problems for partially-observed discrete event systems where sensor readings are assumed to be costly for reasons of bandwidth, energy, or security. The supervisory controllers, or agents, dynamically request sensors readings as needed to observe the trajectories of the system and correctly implement the given feedback control law. Thus, each sensor may be turned on/off several times along a given system trajectory. Different policies for dynamic sensor activation can be used by the agents. A set of policies is said to be minimal if any strictly less activation prevents the correct implementation of the control law. A systematic formulation of the dynamic sensor activation problem is proposed and its solution developed when the solution space is restricted to the set of transitions of a given automaton model of the system. Two algorithms that compute minimal sensor activation policies are presented, one for ensuring observability and the other for ensuring coobservability; observability and coobservability are key properties that arise in the solution of supervisory control problems for centralized and decentralized discrete event systems. These algorithms are of polynomial complexity in both the number of states and the number of events of the system.

Formation control of multiple vehicles using dynamic surface control and hybrid systems

This paper deals with the formation control of multiple vehicles, using a combination of dynamic surface sliding control and hybrid systems. Each vehicle must perform several manoeuvres, either independently, or in a coordinated fashion as part of a vehicle formation. A dynamic surface controller is designed for each manoeuvre. Switches between manoeuvres and communication protocols between vehicles are represented using hybrid systems formalisms. Here, we present the design of both independent and coordinated dynamic positioning (DP) controllers for ocean vehicles using dynamic surface control. Independent and coordinated dynamic positioning are manoeuvres that the modules forming a floating runway at sea must perform. Experimental results using scaled modules are shown.