Experiments with Driving Modes for Urban Robots - PowerPoint PPT Presentation

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Experiments with Driving Modes for Urban Robots

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Experiments with Driving Modes for Urban Robots. Carnegie Mellon University. TRM team: ... Failure Modes and Remaining Issues. Experiments Description. Ft. Sam ... – PowerPoint PPT presentation

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Title: Experiments with Driving Modes for Urban Robots


1
  • Experiments with Driving Modes for Urban Robots
  • Carnegie Mellon University
  • TRM team
  • JPL
  • USC
  • IS Robotics
  • Oakridge Natl. Lab.

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6
Algorithm Overview
To driving subsystem
Goal selection Initial template
Omni image
Virtual image
Predicted template location
Local search
Affine registration
Expanded search
Global search
7
Outline
  • Experiments Description
  • Performance Summary
  • Practical Issues
  • Template Selection
  • Template Update
  • View Transfer
  • Recovery Modes
  • Lighting Issues
  • Failure Modes and Remaining Issues

8
Experiments Description
  • Ft. Sam Houston experiments
  • Prior testing at CMU

9
Examples
  • Halfway toward the back of the building
  • Turning toward the corner near the exterior stairs

10
Experiments Performance Summary
  • Designation distance from 60m (back of building)
    to lt 10m (exterior staircase.)
  • Maximum obstacle drop 10 curb, 10 obstacles
    (bricks, rocks, etc.)
  • Terrain roughness Approx. 1 roughness
    amplitude.
  • Slope variation Approx. 20o.
  • Lighting conditions 8am to 8pm sun orientation.
    Bright sun to cloudy conditions.
  • Speed from 0.8 m/s on straight and shallow arcs
    to 0.2m/s for tighter arcs. Turns at 30o/s.
  • Image size Virtual image 300 by 200 pixels, 90o
    field of view.

11
Template Size
12
Template Size
50 pixels
40 pixels
30 pixels
13
Computation Time
  • Computation time as function of template size
    (Pentium 166MHz vision stack.)
  • Distribution
  • Correlation 40
  • Affine tracking 20
  • Unwarping 10
  • Smoothing, blooming removal, transformations
    30

14
Template Update
  • Large variations in scale and orientation
    Periodic update of template
  • Threshold for template re-initialization current
    size gt 1.5 initial size
  • Heuristic for template update Shrink template
    toward the center.
  • Servoed direction is maintained toward the center
    of the target.

15
Template Update Example
Initial target
Target reaches maximum change in scale in the
horizontal direction
Target is re-scaled horizontally
16
Template Update
Target adjustment
17
Template Update
18
View Transfer
  • Virtual image /- 45o
  • View transfer Virtual panning using omnicam
    unwarping
  • Virtual views pre-computed at 45o and 20o
    intervals
  • View transfer has near-zero cost

Target moved to virtual image 2, 45o off
Target
Target inside virtual image 1
1
2
Omnicam virtual spherical view
19
View Transfer Example
  • Transfer example from 90o turn toward the corner
    of the building near the exterior stairs.

Target moves out of current virtual view
Target re-initialized in closest virtual view
(45o virtual camera pan)
20
Recovery Modes
  • Full 6-dof tracking sensitive to rough motion
  • Obstacles
  • Fast point turns
  • Direct correlation search added 32 pixels around
    predicted location of the template.
  • Local search increased to 64 pixels around
    predicted location if target is lost
  • Additional search in /- 45o region

21
Recovery Example
Normal tracking search window is /- 16 pixels
around current target position.
Recovery search search window is increased to
/- 32 pixels. Box shows region swept by the
upper left corner of target in the search region.
Recovered target after template initialization.
22
Lighting Issues
  • Harsh lighting conditions Blooming
  • Solution Interpolation algorithm
  • Evaluation Tracking in a variety of weather
    conditions

Interpolation algorithm
Blooming artifact
23
Issues
  • Integration with other behaviors
  • Computational issues
  • Frequency of global search events
  • Lighting issues
  • Dynamic mixing conventional cameras/omnidirectiona
    l cameras
  • Use of range info from stereo
  • Use of robot state info
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