Autonomous drone behavior via MCDM of UFOMap layers

Daniel R. Buffum; Andrew R. Buck; Jack Akers; Raub Camaioni; Matthew Deardorff; Derek T. Anderson; Robert H. Luke III

doi:10.1117/12.3013540

10 June 2024 Autonomous drone behavior via MCDM of UFOMap layers

Daniel R. Buffum, Andrew R. Buck, Jack Akers, Raub Camaioni, Matthew Deardorff, Derek T. Anderson, Robert H. Luke III

Proceedings Volume 13037, Geospatial Informatics XIV; 130370A (2024) https://doi.org/10.1117/12.3013540
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

Coupling (semi-)autonomous drones with on-ground personnel can help improve metrics like mission safety, task effectiveness, and task completion time. However, in order for a drone to be an effective companion, it needs to be able to make intelligent decisions about what to do in a partially observable and dynamic environment in light of uncertainty and multiple competing criteria. One simple example is where and how to move. These kinds of continuous or waypoint-based decisions vary greatly from task to task, such as in the scenario of building a 3D map of an area, getting a minimum number of pixels on objects for automatic target detection, exploring an area around a search team, etc. While it is possible to implement each behavior from scratch, we discuss a flexible and extensible framework that allows the specification of dynamic, controlled, and explainable behaviors based on the multi-criteria decision making (MCDM), an aggregation task, of different UFOMap voxel map layers. While we currently employ specific layers such as drone position, time since a voxel was last observed, minimum distance to a voxel, and exploration fringe, future additional layers present the opportunity for the creation of more complex and novel behaviors. Through testing with simulated flights, we have demonstrated that such an approach is feasible for the construction of useful semi-autonomous behaviors in the pursuit of human-robot teaming.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Daniel R. Buffum, Andrew R. Buck, Jack Akers, Raub Camaioni, Matthew Deardorff, Derek T. Anderson, and Robert H. Luke III "Autonomous drone behavior via MCDM of UFOMap layers", Proc. SPIE 13037, Geospatial Informatics XIV, 130370A (10 June 2024); https://doi.org/10.1117/12.3013540

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available