Adaptive Levels of Autonomy (ALOA) for UAV Supervisory Control
Abstract
An architecture tor testing and evaluating different methods for adaptive levels of autonomy was devised. We defined multiple Levels of Autonomy (LOA) for each of four operator tasks: allocation, route planning, imagery analysis, and weapon control. To demonstrate the architecture and LOA implementation, we designed a prototype Multi-UAV Control Station Emulator research test bed, by building on existing ORCA-developed software components. ORCA's extensive internal IR&D over several years has produced state-of-the-art automated mission planning tools that allow fully autonomous execution of operator tasks. Experience with operators through the J-UCAS effort and other programs gives us first-hand knowledge of the tools and decision aids operators need when building and assessing mission plans, which support manual mission planning. With this experience, we implemented the two autonomy extremes: manual and fully autonomous and we defined and implemented intermediate levels of autonomy (requires using characteristics of both manual and autonomous task execution for the four operator tasks noted above.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2005
- Accession Number
- ADA437269
Entities
People
- Dan Goldberg
- Michael Chiu
- Michael Leen
- Rubin Johnson