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Scientific Systems Company, Inc

Scientific Systems Company, Inc. Presentation at Meeting No. 96 Aerospace Control and Guidance Systems Committee Harbour Town Resorts Hilton Head, S. Carolina 19-21 October, 2005 By Raman K. Mehra Phone: 781-933-5355 Email: rkm@ssci.com.

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Scientific Systems Company, Inc

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  1. Scientific Systems Company, Inc Presentation at Meeting No. 96 Aerospace Control and Guidance Systems Committee Harbour Town Resorts Hilton Head, S. Carolina 19-21 October, 2005 By Raman K. Mehra Phone: 781-933-5355 Email: rkm@ssci.com

  2. VISTA: Visual Threat Awareness for Unmanned Air Vehicles

  3. VISTA Overview Problem:Situational awareness is required for “nap of the earth” UAV autonomy Goal:Research, design and flight test a system for real time, visual collision obstacle detection Proposed solution: Real time stereo + Perceptual organization + Image segmentation + Region tracking = VISTA (Visual Threat Awareness) system

  4. Challenges of UAV visual obstacle detection • 3D Reconstruction: Difficulty of computing 3D scene structure from two or more 2D images • Performance tradeoffs • Missed detections and false alarms vs. available computation • Scene resolution vs. available computation • Stereo vision: correspondence errors due to low contrast, occlusions, specular reflections, foreshortening, periodic features, threshold choice, minimum distance violation • Traditional block matching stereo is too noisy for practical use in general!

  5. VISTA Achievements • First application of 640x480@23Hz stereo in UAV flight • Real time (3-5Hz) perception algorithm accelerated by Sarnoff Corp’s Acadia I vision processor for improved performance over traditional stereo • Proof of concept visual obstacle detection and avoidance in two flight experiments on Georgia Tech’s GT-Max helicopter against rural obstacles Obstacle Map: Green = Nearest Collision Obstacle, Yellow = Obstacle Disparity Map: Light = Close, Dark = Far, White = Undefined

  6. VISTA Architecture • Stereo: Large baseline (50cm) binocular stereo for range measurement • Foveation: Compression appropriate for collision detection • Segmentation: Measurement fusion, Grouping for obstacle hypotheses • Detection: False alarm rejection, Obstacle tracking

  7. Segmentation examples Synthetic Sign Synthetic Sphere Building Hallway Small Tree Large Tree

  8. Flight experiment 1.1.10: Detection video Disparity Map: Light = Close, Dark = Far, White = Undefined Obstacle Map: Green = Nearest Collision Obstacle, Yellow = Tracked obstacles

  9. Flight experiment 2: Detection and avoidance Flight 2.1.6 Flight 2.2.5 Avoidance Triggered Avoidance Triggered

  10. Flight experiment 2.1.6: Ground video

  11. Flight experiment 2.1.6: Detection video Disparity Map: Light = Close, Dark = Far, White = Undefined Obstacle Map: Green = Nearest Collision Obstacle, Yellow = Tracked obstacles

  12. VISTA Summary Major Accomplishments: • First application of 640x480@23Hz stereo hardware in UAV flight • Real time (3-5Hz) algorithm that improves collision obstacle detection performance over traditional stereo only • Proof of concept in two flight experiments against real obstacles. We have demonstrated proof of concept for a real time visual collision detection system in a rural environment.

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