Abstract: A system and method for controlling movement of a vehicle. A current state of the vehicle is identified. The current state comprises a current location of the vehicle. A next state for the vehicle is selected by a processor unit. The next state comprises a next location for the vehicle. A value for an attribute of the next state of the vehicle is randomly selected. The movement of the vehicle is controlled to move the vehicle from the current state to the next state.

Abstract: A system and methods for autonomously tracking and simultaneously providing surveillance of a target from air vehicles. In one embodiment the system receives inputs from outside sources, creates tracks, identifies the targets and generates flight plans for unmanned air vehicles (UAVs) and camera controls for surveillance of the targets. The system uses predictive algorithms and aircraft control laws. The system comprises a plurality of modules configured to accomplish these tasks. One embodiment comprises an automatic target recognition (ATR) module configured to receive video information, process the video information, and produce ATR information including target information. The embodiment further comprises a multisensor integrator (MSI) module configured to receive the ATR information, an air vehicle state input and a target state input, process the inputs and produce track information for the target.

Abstract: An enhanced control system for an unmanned aerial vehicle adds constraints to the process of choosing a flight path in the event of an in-flight contingency, such as engine out or an encounter with jamming, which forces a diversion or unplanned landing. The constraints are: (1) ensure communications are available when needed during contingency operations; and (2) ensure signals from a global positioning system (or other navigation system) are available when needed during contingency operations.

Abstract: A system and method for controlling movement of a vehicle. A current state of the vehicle is identified. The current state comprises a current location of the vehicle. A next state for the vehicle is selected by a processor unit. The next state comprises a next location for the vehicle. A value for an attribute of the next state of the vehicle is randomly selected. The movement of the vehicle is controlled to move the vehicle from the current state to the next state.

Abstract: A system and methods for autonomously tracking and simultaneously providing surveillance of a target from air vehicles. In one embodiment the system receives inputs from outside sources, creates tracks, identifies the targets and generates flight plans for unmanned air vehicles (UAVs) and camera controls for surveillance of the targets. The system uses predictive algorithms and aircraft control laws. The system comprises a plurality of modules configured to accomplish these tasks. One embodiment comprises an automatic target recognition (ATR) module configured to receive video information, process the video information, and produce ATR information including target information. The embodiment further comprises a multi-sensor integrator (MSI) module configured to receive the ATR information, an air vehicle state input and a target state input, process the inputs and produce track information for the target.

Abstract: A system and method for controlling movement of a vehicle. A current state of the vehicle is identified. The current state comprises a current location of the vehicle. A next state for the vehicle is selected by a processor unit. The next state comprises a next location for the vehicle. A value for an attribute of the next state of the vehicle is randomly selected. The movement of the vehicle is controlled to move the vehicle from the current state to the next state.

Abstract: A system and method for controlling movement of a vehicle. A current state of the vehicle is identified. The current state comprises a current location of the vehicle. A next state for the vehicle is selected by a processor unit. The next state comprises a next location for the vehicle. A value for an attribute of the next state of the vehicle is randomly selected. The movement of the vehicle is controlled to move the vehicle from the current state to the next state.

Abstract: A method of protecting an asset using at least one unmanned vehicle. The method includes establishing a plurality of boundaries around the asset. The boundaries define edges of zones. The method further includes observing a target in a first one of the zones. The method further includes deploying the unmanned vehicle to a location in a vicinity of the asset and tasking the vehicle to perform a first defensive measure as long as the target remains in the first zone. If the target crosses a boundary from the first zone into a second one of the zones, where the second zone is more proximate to the asset than the first zone, the method further includes tasking the vehicle to perform a second defensive measure.

Abstract: A system and methods for autonomously tracking and simultaneously providing surveillance of a target from air vehicles. In one embodiment the system receives inputs from outside sources, creates tracks, identifies the targets and generates flight plans for unmanned air vehicles (UAVs) and camera controls for surveillance of the targets. The system uses predictive algorithms and aircraft control laws. The system comprises a plurality of modules configured to accomplish these tasks. One embodiment comprises an automatic target recognition (ATR) module configured to receive video information, process the video information, and produce ATR information including target information. The embodiment further comprises a multi-sensor integrator (MSI) module configured to receive the ATR information, an air vehicle state input and a target state input, process the inputs and produce track information for the target.