David W. Casbeer

Cooperative forest fire surveillance using a team of small unmanned air vehicles

The objective of this paper is to explore the feasibility of using multiple low-altitude, short endurance (LASE) unmanned air vehicles (UAVs) to cooperatively monitor and track the propagation of large forest fires. A real-time algorithm is described for tracking the perimeter of fires with an on-board infrared sensor. Using this algorithm, we develop a decentralized multiple-UAV approach to monitoring the perimeter of a fire. The UAVs are assumed to have limited communication and sensing range. The effectiveness of the approach is demonstrated in simulation using a six degree-of-freedom dynamic model for the UAV and a numerical propagation model for the forest fire. Salient features of the approach include the ability to monitor a changing fire perimeter, the ability to systematically add and remove UAVs from the team, and the ability to supply time-critical information to fire fighters.

Forest fire monitoring with multiple small UAVs

Frequent updates concerning the progress of a forest fire are essential for effective and safe fire fighting. Since a forest fire is typically inaccessible by ground vehicles due to mountainous terrain, small unmanned air vehicles (UAVs) are emerging as a promising means of monitoring large forest fires. We present an effective UAV path planning algorithm utilizing infrared images that are collected on-board in real-time. To demonstrate the effectiveness of our path planning algorithm in realistic scenarios, we simulated the propagation of a forest fire with the EMBYR model. A new cooperative control mission concept is introduced where multiple low-altitude, short-endurance (LASE) UAVs are used for fire monitoring. By employing multiple UAVs, the effectiveness of the mission in terms of information update rate can be improved dramatically.

Decentralised event-triggered cooperative control with limited communication

This note studies event-triggered control of Multi-Agent Systems (MAS) with first-order integrator dynamics. It extends previous work on event-triggered consensus by considering limited communication capabilities through strict peer-to-peer non-continuous information exchange. The approach provides both a decentralised control law and a decentralised communication policy. Communication events require no global information and are based only on local state errors; agents do not require a global sampling period or synchronous broadcasting as in sampled-data approaches. The proposed decentralised event-triggered control technique guarantees that the inter-event times for each agent are strictly positive. Finally, the ideas in this note are used to consider the practical scenario where agents are able to exchange only quantised measurements of their states.

Decentralized event-triggered consensus with general linear dynamics

The consensus problem with general linear dynamics and undirected graphs is studied in this paper by means of event-triggered control strategies. A novel consensus protocol is proposed, where each agent implements a model of the decoupled dynamics of its neighbors. Under this control strategy, transmission of information does not occur continuously but only at discrete points in time. The approach presented in this paper provides both a decentralized control law and a decentralized communication policy. We are able to design thresholds that only depend on local information and guarantee asymptotic consensus. Positive inter-event times are guaranteed for particular cases of the linear dynamics. In an extension, a positive constant is added to the thresholds in order to exclude Zeno behavior for general linear dynamics. The difference between agents trajectories can be bounded in this case and bounds on the state disagreement are derived.

Distributed information filtering using consensus filters

In this paper we present a new information consensus filter for distributed dynamic-state estimation. Estimation is handled by the traditional information filter, while communication of measurements is handled by a consensus filter. First and second-order statistics of local estimates are discussed. It is shown that local information consensus filter estimates are unbiased, and the actual variance of the local estimation errors is comparable to a centralized estimate. However, local agents believe their local estimates are less accurate.

Discrete double integrator consensus

A distributed double integrator discrete time consensus protocol is presented along with stability analysis. The protocol will achieve consensus when the communication topology contains at least a directed spanning tree. Average consensus is achieved when the communication topology is strongly connected and balanced, where average consensus for double integrator systems is discussed. For second order systems average consensus occurs when the information states tend toward the average of the current information states not their initial values. Lastly, perturbation to the consensus protocol is addressed. Using a designed perturbation input, an algorithm is presented that accurately tracks the center of a vehicle formation in a decentralized manner.

Circumnavigation of an unknown target using UAVs with range and range rate measurements

This paper presents two control algorithms enabling a UAV to circumnavigate an unknown target using range and range rate (i.e., the derivative of range) measurements. Given a prescribed orbit radius, both control algorithms (i) tend to drive the UAV toward the tangent of prescribed orbit when the UAV is outside or on the orbit, and (ii) apply zero control input if the UAV is inside the desired orbit. The algorithms differ in that, the first algorithm is smooth and unsaturated while the second algorithm is non-smooth and saturated. By analyzing properties associated with the bearing angle of the UAV relative to the target and through proper design of Lyapunov functions, it is shown that both algorithms produce the desired orbit for an arbitrary initial state. Two examples are provided as a proof of concept.

Adaptive Mobile Sensor Positioning for Multi-Static Target Tracking

Unmanned air vehicles (UAVs) are playing an increasingly prominent role in both military and civilian applications. We focus here on the use of multiple UAV agents in a target tracking application where performance is improved by exploiting each agents maneuverability. Local time-delay and Doppler measurements made at each UAV are used as inputs to an extended Kalman filter (EKF) which tracks the targets position and velocity. Two simple metrics are defined to quantify the accuracy of the tracking algorithm, and heading feedback to the UAVs is used to minimize the metric and improve tracking performance. A simplified version of one of the algorithms that reduces computational complexity is also presented. Simulations demonstrate the significant improvement that results when the UAV sensors are allowed to be optimally positioned during tracking.

An extension of consensus-based auction algorithms for decentralized, time-constrained task assignment

This paper addresses the multi-target, multi-task assignment problem for unmanned vehicles by presenting the decentralized Extended Consensus-Based Bundle Algorithm (ECBBA). The algorithm converges to conflict-free feasible solutions; furthermore, the algorithm allows local “pop-up” targets to be added and re-converges to a solution without resolving the entire optimization. A method to limit the communication network around targets is introduced. Limiting the communication is shown, through simulation, to produce solutions commensurate with full communication (within 2%) with the added benefit of reduced communication across the network.

Cooperative aircraft defense from an attacking missile

This paper addresses a three-body pursuit-evasion scenario where an Attacker missile using Pure Pursuit guidance pursues a Target aircraft and a Defender missile launched by a wingman aims at intercepting the Attacker before it reaches the aircraft. An optimal control problem is posed which captures the goal of the Target-Defender team, namely, to maximize the separation between Target and Attacker at the instant of capture of the Attacker by the Defender. The optimal control law provides the heading angles for the Target and the Defender team.