|Student Name:||Capt Charles Neal|
|Thesis:||Feasibility of Onboard Processing of Heuristic Path Planning and Navigation Algorithms Within SUAS Autopilot Computational Constraints|
|Location:||Bldg 640, Room 353 (ENY CR)|
|Attendance Restrictions:||Distribution A. Unlimited Distribution.|
|Date & Time:||02/27/2014 at 1500|
|Abstract:|| This research addresses the flight path optimality of Small Unmanned Aerial Systems (SUAS) conducting overwatch missions for convoys or other moving ground targets. Optimal path planning tools have been proposed, but are currently used for post-processing as they are computationally excessive for real-time execution. Using a commercial Unmanned Aerial Vehicle (UAV) autopilot system, Hardware-in-the-Loop (HIL) analysis is conducted on default mobile target tracking methods. Designed experimentation is used to determine autopilot settings that improve performance with respect to path optimality. Optimality is defined as a weighted combination of stand-off range and aircraft roll-rate. Finally, a state-based heuristic navigation strategy is designed, developed, and tested that approximates optimal path solutions and can be used for real-time execution. Statistically significant performance increases are achieved and it is concluded that heuristic strategies can be a viable approach to realizing near-optimal SUAS flight paths utilizing onboard processing capabilities.