Enhancing Capabilities and Reducing Workload in UAV Operations. Zahar Prasov NDIA Human Systems Conference February 09-10, 2016
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1 Enhancing Capabilities and Reducing Workload in UAV Operations Zahar Prasov NDIA Human Systems Conference February 09-10, 2016
2 Background ISR Missions Support Small Crew of UAV Operators 2
3 Challenges High Operational Cost 3-Operator Crew : 1 UAV Waypoint Navigation 3
4 Ideal Scenario Supervisory Control of Multiple UAVs Pooled Resource Allocation (U.S. Air Force photo by Val Gempic/Released) Enhanced Mission Capability 4
5 How to achieve the ideal scenario? 1. Enhance effectiveness of single UAV (single crew) missions 2. Reduce operational cost 3. Multi-UAV operations 5
6 How to achieve the ideal scenario? 1. Enhance effectiveness of single UAV (single crew) missions 2. Reduce operational cost 3. Multi-UAV operations Solution Approach via Multi- Agent Autonomous Reusable Software (MAARS) 6
7 Workflow Analysis Pilot Mission Commander Payload Operator (U.S. Air Force photo by Val Gempic/Released) 7
8 Mission Stakeholders Pilot Mission Commander Air Traffic Control Payload Operator (U.S. Air Force photo by Val Gempic/Released) (U.S. Air Force photo by Val Gempic/Released) Analysts 8
9 Information Flow Pilot Air Traffic Control Mission Commander Analysts Payload Operator Voice 9
10 The Mission Commander is Overloaded! Pilot Air Traffic Control Mission Commander (DARPA Insight Photo Illustration) Analysts Payload Operator Voice 10
11 Primarily Voice-Based Coordination Pilot Air Traffic Control Mission Commander Analysts Payload Operator Voice 11
12 Enhance Current Single Crew/UAV Operations Reduce Mission Commander Load: Waypoint navigation high-level mission planning Voice-based coordination digitally-assisted coordination 12
13 via MAARS Comms Multi-Agent Autonomous Reusable Software Sensors Autopilot 13
14 MAARS Architecture Comms MAARS Sensors Autopilot 14
15 Capabilities Developed in MAARS Adherence to geospatial constraints Avoiding terrain Maintaining communication Adherence to mission constraints Ground-target following Airspace management 15
16 Adherence to Geospatial Constraints Line-of- Sight Avoidance Zone Terrain Avoidance Zone 16
17 Adherence to Geospatial Constraints Pilot Air Traffic Control Mission Commander Analysts Payload Operator MAARS Redundant Voice 17
18 Ground-Target Following Payload Interaction Potential Target Field of View 18
19 Ground-Target Following Payload Interaction Autonomy Visualization Interaction 19
20 Ground-Target Following Planned Transit Active Transit Autonomy Visualization Interaction 20
21 Ground-Target Following Pilot Air Traffic Control Mission Commander Analysts Payload Operator Ground Target Status MAARS Redundant Voice 21
22 Airspace Management Denied Approved Unspecified 22
23 Airspace Management Denied Approved Unspecified Re-routed path Active Transit 23
24 Airspace Management Pilot Air Traffic Control Mission Commander Analysts Payload Operator MAARS Redundant Voice 24
25 Resulting Workflow: Reduction in MC and Pilot Load Pilot Air Traffic Control Mission Commander Analysts Payload Operator Ground Target Status MAARS Redundant Voice 25
26 Combine MC/Pilot into One Role Air Traffic Control Mission Commander & Pilot Analysts Payload Operator Ground Target Status MAARS Voice 26
27 Combine MC/Pilot into One Role Reduction in Operational Cost Mission Commander & Pilot Air Traffic Control Analysts Payload Operator Ground Target Status MAARS Voice 27
28 Future Work Enable Single Crew to Perform multi-uav Operations Enable Dynamic (real-time) Mission Planning 28
29 Acknowledgements Contributors: Dr. Rahul Chipalkatty Matt Grammes Tim Gomeringer Arch Owen Contact: Dr. Zahar Prasov Research Engineer Draper
30 Thank You! Questions? 30
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