Cooperative operations in urban terrain (COUNTER)

Abstract

The Air Force Research Laboratory (AFRL) has an ongoing investigation to evaluate the behavior of Small Unmanned Aerial Vehicles (SAVs) and Micro Aerial Vehicles (MAVs) flying through an urban setting. This research is being conducted through the Cooperative Operations in UrbaN TERrain (COUNTER) 6.2 research and flight demonstration program. COUNTER is a theoretical and experimental program to develop the technology needed to integrate a single SAV, four MAVs, and a human operator for persistent intelligence, reconnaissance and surveillance for obscured targets in an urban environment. The research involves development of six-degree-of-freedom models for integration into simulations, modeling and integration of wind data for complex urban flows, cooperative control task assignment and path planning algorithms, video tracking and obstacle avoidance algorithms, and an Operator Vehicle Interface (OVI) system. The COUNTER concept and the contributing technologies will be proven via a series of flight tests and system demonstrations.The first of six planned COUNTER flight demonstrations occurred in July of 2005. This demonstration focused on the simultaneous flight operations of both the SAV and the MAV while displaying their respective telemetry data on a common ground station (OVI). Current efforts are focused on developing the architecture for the Cooperative Control Algorithm. In FY 2006, the COUNTER program will demonstrate the ability to pass vehicle waypoints from the OVI station to the SAV and MAV vehicles. In FY 2007, the COUNTER program will focus on integrating solutions to the optical target tracking (SAV) and obstacle avoidance (MAV) issues into the capabilities of the OVI station and Cooperative Control Algorithm.

Approximate dynamic programming with state aggregation applied to UAV perimeter patrol

“…Note that computing V˜ 1 via a policy evaluation step is expensive, as noted before (11). Strictly speaking, it is not necessary, except for computing the bounds in (27) to assess the quality of the approximation.…”

“…This problem is motivated by the perimeter patrol problem that arose out of the Cooperative Operations in UrbaN TERrain (COUNTER) project at the Air Force Research Laboratory (AFRL) [11,12]. In this problem, there is a perimeter that must be monitored by a team of UAVs (we will consider only one UAV here).…”

An analysis of wind field estimation and exploitation for quadrotor flight in the urban canopy layer

“…Orr et al [9], [10] used a computational fluid dynamics (CFD) solver to generate static wind fields and assess the waypoint following performance of a fixed-wing UAV. Another effort was made by Galway [11], [12] to simulate an autonomous helicopter in a sparse urban environment.…”

State aggregation based linear programming approach to approximate dynamic programming

“…for all u ∈ U which appears to suggest that (since β > 0), satisfying just the first constraint i.e., the one corresponding to t j k = 1 ensures that all the constraints in (19) are met. This turns out to be true for the problem under consideration (corroborated by numerical evidence)!…”

“…We shall showcase the partitioning approach using the perimeter patrol problem that arose out of the Cooperative Operations in Urban Terrain (COUNTER) project at the Air Force Research Laboratory (AFRL) [19], [20]. In this problem, there is a closed perimeter which must be monitored by a collection of UAVs (we will consider only one UAV here).…”