Effective command and control of unmanned aerial vehicles (UAVs) is an issue under investigation as the military pushes toward more automation and incorporation of technology into their operational strategy. UAVs require the intelligence to maneuver safely along a path to an intended target while avoiding obstacles such as other aircraft or enemy threats. To date, path-planning algorithms (designed to aid the operator in the control of semi-autonomous UAVs) have been limited to providing only a single solution (alternate path) without utilizing input or feedback from the UAV operator. The work presented in this thesis builds off of and improves an existing path planner. The original path planner presents a unique platform for decision making in a three-dimensional environment where multiple solution paths are generated using Particle Swarm Optimization (PSO) and returned to the operator for evaluation. The paths are optimized to minimize risk due to enemy threats, to minimize fuel consumption incurred by deviating from the original path, and to maximize reconnaissance over predefined targets. The work presented in this thesis focuses on improving the mathematical models of these objectives. Terrain data is also incorporated into the path planner to ensure that the generated alternate paths are feasible and at a safe height above ground.

An effective interface is needed to evaluate the alternate paths returned by PSO. A "meta-path" is a new concept presented in this thesis to address this issue. Meta-paths allow an operator to explore paths in an efficient and organized manner by displaying multiple alternate paths as a single path cloud. The interface was augmented with more detailed information on these paths to allow the operator to make a more informed decision. Two other interaction techniques were investigated to allow the operator more interactive control over the results displayed by the path planner. Viewing the paths in an immersive environment enhances the operator's understanding of the situation and the options while facilitating better decision making. The problem formulation and solution implementation are described along with the results from several simulated scenarios. Preliminary assessments using simulated scenarios show the usefulness of these features in improving command and control of UAVs.

Finally, a user study was conducted to gauge how different visualization capabilities affect operator performance when using an interactive path planning tool. The study demonstrates that viewing alternate paths in 3D instead of 2D takes more time because the operator switches between multiple views of the paths but also suggests that 3D is better for allowing the operator to understand more complex situations.