25th Annual Student Research Conference
Dynamic Sparse A* Search for Collision Avoidance in Autonomous Unmanned Aerial Vehicles
Tyler A. Young* and Andrew J. Kaizer
Dr. Alan Garvey, Faculty Mentor
In order for autonomous unmanned aerial vehicles (UAVs) to be widely adopted in civilian airspace, they must be capable of safe, autonomous flight. The problem of collision avoidance in UAVs is discussed in its theoretical foundations, and an overview is given of the methods of collision avoidance and path planning most widely represented in the literature. The authors' own approach--an adaptation of A* search for use with dynamic obstacles, such as other UAVs--is discussed in depth. This algorithm, termed Dynamic Sparse A*, is considered in terms of both the underlying theory and the actual implementation. The benefits, drawbacks, and potential applications of the algorithm are also considered.
Keywords: search, artificial intelligence, computer science, UAVs
Topic(s):Computer Science
Presentation Type: Oral Paper
Session: 210-4
Location: VH 1228
Time: 10:15