Autonomous Decision Support for Unmanned Vehicle Control in a Multi-vehicle, Multi-domain Environment

Period of Performance: 10/31/2012 - 05/06/2013


Phase 1 SBIR

Recipient Firm

Soar Technology, Inc.
3600 Green Court Array
Ann Arbor, MI 48105
Principal Investigator


SoarTech will research technologies to address a fundamental problem in current unmanned vehicle operations reduction in the amount of operator attention required to control a team of unmanned vehicles (UVs). We call our approach Lucid, and the Lucid system will monitor the mission and behavior of a team of heterogeneous UVs and 1. automate the presentation of salient information to the user 2. detect and project important events and alert the user to them, 3. provide context-relevant, high-level inputs, making some actions as simple as one click, and 4. assess user C2 effectiveness, helping to automate task distribution based on context. Lucid will enable supervisory control allowing operators to spend less time interacting with the system and more time doing other important tasks. To achieve these results Lucid will implement computational situation awareness (CSA), and use it as a basis for intelligent UI control, decision support, and high-level command inputs. The core concepts behind Lucid were prototyped and tested in the MAGIC International Robot Competition where SoarTech teamed with the University of Michigan to win in 2010. Lucid will build on that ground-breaking work by incorporating the naval domain, CSA, C2 effectiveness estimation, and high level command into this framework.