real-time configuration space transforms for obstacle avoidance
DESCRIPTION
Real-Time Configuration Space Transforms for Obstacle Avoidance . Wyatt S. Newman and Michael S. Branicky. Summary. Explicit computation of configuration space Useful for planning and control “Primitives” allow for generalization across environments Points, lines, circles 3D equivalents - PowerPoint PPT PresentationTRANSCRIPT
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Real-Time Configuration Space Transforms for Obstacle Avoidance
Wyatt S. Newman and Michael S. Branicky
![Page 2: Real-Time Configuration Space Transforms for Obstacle Avoidance](https://reader035.vdocument.in/reader035/viewer/2022062410/56816384550346895dd46bfc/html5/thumbnails/2.jpg)
Summary• Explicit computation of
configuration space– Useful for planning and
control• “Primitives” allow for
generalization across environments– Points, lines, circles– 3D equivalents
• Techniques are not general across manipulators– Derived for 2 kinds in the
paper
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Key Properties• Set Union Property
– The two Cobs of two obstacles, is the union of the Cobs of each
– Allows the authors to build up complicated Cobs out of simple primitives
• Set Containment Property– If an obstacle is contained inside another,
only the C-space of the outer one matters
– The authors only have to consider the boundaries of obstacles
![Page 4: Real-Time Configuration Space Transforms for Obstacle Avoidance](https://reader035.vdocument.in/reader035/viewer/2022062410/56816384550346895dd46bfc/html5/thumbnails/4.jpg)
Key Properties• Set Union Property
– The two Cobs of two obstacles, is the union of the Cobs of each
– Allows the authors to build up complicated Cobs out of simple primitives
• Set Containment Property– If an obstacle is contained inside another,
only the C-space of the outer one matters
– The authors only have to consider the boundaries of obstacles
![Page 5: Real-Time Configuration Space Transforms for Obstacle Avoidance](https://reader035.vdocument.in/reader035/viewer/2022062410/56816384550346895dd46bfc/html5/thumbnails/5.jpg)
Points• Two link planar manipulator• Point obstacle at distance d from the origin on the x-axis• Link 1 only collides at θ1=0• Link 2 collisions are computed using inverse kinematics for a series of points
along the link
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Points• Translation property
– If the point is not on the x-axis, it just shifts this c-space shape– e.g. If the point is at a 45 degree angle from the x-axis, then the shape
will be centered around θ1=45 degrees
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Lines
• A line is just a series of points (union property)
• The authors show what happens for a line normal to the x-axis and distance d from the origin
• These circles are actually filled in, but because of the containment property we only have to worry about borders
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Line Segments
• Just as a point splits a line in workspace, the curve formed in c-space by that point splits the shape
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Line Segments
• A line segment has 2 such points• The resulting c-space obstacle is the set of curves in
between
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Line Segments
• A line segment has 2 such points• The resulting c-space obstacle is the set of curves in
between
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Real Robot Example
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Real Robot Example
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Circles
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Generalization to 3D
• Points, lines, and circles generalize to points, planes, and spheres
• Done for a R-R planar manipulator with a base joint that changes the “slice” (plane)
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Nice Insight
• “For serial links numbers sequentially from the ground to the most distal link, link “i” obstacles require an i-dimensional configuration space representation.”
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Limitations• The translation properties in
this paper are specific to the kinematics of the manipulator
• It only generalizes to 3D in certain cases
• Even the shown extension to 3D is a little forced if the links have non-negligible width– The “slices” are an
oversimplification• This appears to get intractable
quickly– The authors only go up to 3DoF
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How to update it?
• Computing high-dimensional c-space is expensive even today
• If explicit c-space is really needed, it can be approximated with a sampling method (like PRMs)