Pictures by NASA, ESA, and The Hubble Heritage Team (STScI

Pictures by NASA, ESA, and The
Hubble Heritage Team (STScI/AURA)
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Picture by NASA
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Sensors for On-Orbit Docking
Stephen Granade
stephen.granade@dynetics.com
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What Do You Need to Measure?
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Make a Relative Measurement of Six-DoF
y
Orientation (roll, pitch, yaw)
y
yaw
roll
z
pitch
z
x
Position (x, y, z)
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x
How Far Away is Hubble?
Picture by NASA
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Ways of Measuring
Position and
Orientation
A Tale of Two
Approaches
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Direct vs. Indirect Measurement
Direct
Indirect
Picture by Arild Storaas
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Types of Direct and Indirect Measurement
 Direct
 Measure distance directly using light or radar pulses
 Indirect
 Measure x and y position by where the spacecraft is
in an image
 Measure distance (z) by looking at how big the
spacecraft appears in the image
 Measure angles (roll, pitch, yaw) by looking at the
spacecraft’s shape or the relative location of points
on the spacecraft
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Direct: Radar or Laser Rangefinding
y
z
0.3 m/ns
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x
Indirect: Use a Camera to Estimate 6DoF
Position: x, y
Original pictures by NASA
Size: z (distance)
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Shapes or Points:
Orientation
Look At How Shapes Are Distorted to Get Angles
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Apparent Distortion is Related to Angles
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Measure Relative Location of Known Features
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Measure Relative Location of Known Features
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A Camera Makes a 2D Projection of a 3D Scene
Field of View
Lens
Focal Point
Imager (Focal Plane Array)
Warning: Not to scale
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Pixels Correspond To Angular Location
Lens
Imager (Focal Plane Array)
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Perspective Lets You Calculate Angles
Spacecraft
Spacecraft
Camera
Camera
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Shuttle Dockings: Direct & Indirect Measurements
Pictures by NASA
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A Closer Look at the ISS Target
Picture by Advanced Optical Systems
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Locating
Features on
Spacecraft
A Tale of Two Types of
Spacecraft
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Cooperative vs. Uncooperative Spacecraft
Uncooperative
Pictures by NASA
Cooperative
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Cooperative Targets Are (Relatively) Easy
Pictures by DARPA (left) and AOS (right)
Hubble’s Soft Capture Mechanism Included Targets
Pictures by NASA and AOS (inset picture)
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Uncooperative Targets Require Image Recognition
AOS Space Vision
Tracking System
Boeing Vis-STAR
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What Makes For Good Features?
 Individual feature’s
sizes
 Distribution of features
 Widely-spaced side to
side
 Spaced front to back
 Contrast
 Spatially distinctive
 Corners, edges, color
changes
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Choose Your Sensors to Match Your Targets
 Sensors can make direct or indirect
measurements
 Get distance directly using rangefinding with light or
radar
 Get distance indirectly by looking at size of objects
on an image or distance between points on a
spacecraft
 Get orientation indirectly by looking at spacecraft
shape or relative configuration of features (points) on
the spacecraft
 Targets can be cooperative or uncooperative
 Cooperative spacecraft have distinctive features that
are easy to find
 Uncooperative ones require image processing
techniques to recognize features
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Docking Sensors
That Have Flown
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IGLA and KURS
 Russian system
 Multiple radar antennas
 Multi-stage process
 Acquisition: target
spacecraft broadcasts
beacon signal
 Tracking: target spacecraft
re-broadcasts what the
Progress sends
 Works over tens of km
 Most flown relative
navigation system
Pictures by NASA
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Advanced Video Guidance Sensor (AVGS)
 NASA/AOS/Orbital
Sciences system
 Laser-based
 Camera images spots of
light reflected from targets
 Processes spot locations to
determine target’s position
and orientation
 Works to 1 km / 300 m
 Flown on DART and Orbital
Express missions
Pictures by Orbital Sciences/AOS (top),
AOS (inset), and NASA (bottom)
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ARCSS
 Boeing system
 Visible-light and IR
cameras
 Images (including
silhouette and edgeenhanced) correlated
against library images
 Uses features at short
ranges
 Works to 200 km / 60 m
 Flown on Orbital Express
Pictures by Boeing
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Relative Navigation Sensor System
 NASA and AOS system
 Three visible-light cameras
 Matched features in edgeenhanced image against a
model (NASA GNIFR) or
correlated features against
a library (AOS ULTOR)
 Worked to 150 m
 Flown on Hubble Servicing
Mission 4
Pictures by NASA (top and
bottom left) and AOS (bottom right)
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TriDAR
 Neptec system
 Laser rangefinding, laser
triangulation, and an IR
camera
 3D point cloud compared
to models
 Uses IR camera for long
ranges
 Works to ~40 km / 400 m
 Flown on three Shuttle
missions and Cygnus
Pictures by NASA (top) and Neptec (bottom)
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Vision Navigation Sensor (VNS)
 NASA/Ball/Lockheed
Martin system
 Flash LIDAR and visiblelight camera
 Range measurements to
reflective targets
 Visible-light camera for
situational awareness
 Works to 200 km / 60 m
 Flown on a Shuttle mission
Pictures by Ball Aerospace
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Why So Many? Because There’s No “Best” Solution
 Cooperative gives you the most control but
requires modifying the spacecraft you want to
dock with
 Uncooperative is the most flexible, but much
harder to get right
 There is no one image processing solution that works
in all situations
 Because space is a low-volume business, we’re
not seeing big jumps in technology powered by
commercial demand
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Note: Autonomous On-Orbit Docking is Hard
 IGLA: Three failures on orbit, one due to a trash
bag
 KURS: Multiple failures, including one that led to
a Progress hitting Mir, and another that left a
Progress adrift near the ISS
 DART: Failed to turn on AVGS, and hit MUBLCOM
 Orbital Express: Had to adjust ARCSS object
recognition settings on orbit
 Orbital Express and Japan’s ETS-VII: Target
satellite got lost and had to be recovered
 Hubble RNS: GNIFR tracked only at first, ULTOR
not at all while on orbit
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Where Next?
 ISS resupply craft are using docking sensors
 Progress-M: Kurs
 ESA ATV and JAXA HTV: Scanning LIDAR looks for
reflections from targets
 Orbital Express Cygnus: TriDAR
 SpaceX Dragon: developing the DragonEye flash LIDAR
 Orion’s Vision Navigation Sensor is still in the wings
 GSFC RAVEN
 DARPA Phoenix program for satellite servicing
 A few commercial efforts
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Sensors for On-Orbit Docking
Stephen Granade
stephen.granade@dynetics.com
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