accounts for how to determine if a path is obstructed between two grid points when

dealing with three-dimensional contours. The method currently used may not be

sufficient for the three-dimensional problem.

 In addition, this research could be extended to incorporate ground and aerial vehicles.

The system would function as follows:

1. An aerial vehicle would navigate to a desired location or waypoint.

2. Once at the waypoint, a series of photographs would be taken with an onboard
 camera.

3. These photographs would be discretized, similar to the way the maps were as
 presented in this research. The landmarks, obstacles, and boundaries would be
 extracted from the images to create a map.

4. This map would be used and the algorithm would determine the positions for the
 ground robots and the corresponding combined shadow area.

 This is an example of a hybrid collaborative control system. Two specific types of

robots are being controlled to achieve an overall task of maximizing the coverage of a

search space while maintaining communications. This is a very simplified approach to

this problem and there is a great deal of work involved before actual implementation of

this type of system. Some problems are: automation of a small aerial vehicle that is able

to navigate to waypoints, image processing that will extract obstacles from the

photographs taken by the aerial vehicle, and having enough ground vehicles to

accomplish this task.

 This research has provided some initial results for robot coordination and collaborative

control. The results reinforce the validity of the method as well as the technique used for

optimization of the solution. The speed at which a solution is obtained is also an

attractive feature of this algorithm. The genetic algorithm technique for optimization