Sensor networks are gaining a central role in the research community. This paper addresses some of the issues arising from the use of sensor networks in control applications. Classical control theory proves to be insufficient in modeling distributed control problems where issues of communication delay, jitter, and time synchronization between components are not negligible. After discussing our hardware and software platform and our target application, we review useful models of computation and then suggest a mixed model for design, analysis, and synthesis of control algorithms within sensor networks. We present a hierarchical model composed of continuous time-trigger components at the low level and discrete event-triggered components at the high level.

We present a multiple view algorithm for vision based landing of an unmanned aerial vehicle. Our algorithm is based on our results in multiple view geometry which exploit the rank deficiency of the so called multiple view matrix. We show how the use of multiple views significantly improves motion and structure estimation. We compare our algorithm to our previous linear and non-linear two-view algorithms using an actual flight test. Our results show that the vision-based state estimates are accurate to within 7cm in each axis of translation and 4 degrees in each axis of rotation.

We present the design and implementation of a real-time computer vision system for a rotor-craft unmanned aerial vehicle to land onto a known landing target. This vision system consists of customized software and off-the-shelf hardware which perform image processing, segmentation, feature point extraction, camera pan/tilt control, and motion estimation. We introduce the design of a landing target which significantly simplifies the computer vision tasks such as corner detection and correspondence matching. Customized algorithms are developed to allow for realtime computation at a frame rate of 30Hz. Such algorithms include certain linear and nonlinear optimization schemes for model-based camera pose estimation. We present results from an actual flight test which show the vision-based state estimates are accurate to within 5cm in each axis of translation and 5 degrees in each axis of rotation, making vision a viable sensor to be placed in the control loop of a hierarchical flight management system.

Presents the implementation of a hierarchical architecture for the coordination and control of a heterogeneous team of autonomous agents. We consider the problem of having a team of agents pursue a second team of evaders while building a map of the environment. The control architecture emphasizes the autonomy of each agent yet allows for coordinated efforts among them. We address the technical challenges and implementation issues of multi-agent operation. Finally we present experimental results of a pursuit-evasion game scenario between unmanned ground and aerial vehicles.