Date of Graduation
Statler College of Engineering and Mineral Resources
Mechanical and Aerospace Engineering
Marcello R. Napolitano.
The effort of this research is to move toward enabling Unmanned Air Vehicles to fly in autonomous formations with intelligent mission planning capabilities. In particular, UAVs will be able to autonomously perform path planning and task allocation. During missions, the UAVs must be able to avoid threats and no-fly zones while still reaching their target optimally in time.;A path planning and task allocation approach was first developed that treats the problem as a Multi-dimensional, Multiple-Choice Knapsack Problem. Paths are selected and task assigned while minimizing the UAV team's overall mission cost. Next, a SIMULINK-based centralized simulation environment was created. This simulation uses the path planning and task allocation scheme previously developed, and adds time-varying, dynamic environment aspects. The latter part of the research effort was focused on development of a decentralized simulation environment. This decentralized version includes a vehicle's own decision making capabilities and communication amongst a team of vehicles. (Abstract shortened by UMI.).
Lechliter, Matthew C., "Decentralized control for UAV path planning and task allocation" (2004). Graduate Theses, Dissertations, and Problem Reports. 1443.