Laboratory for Perceptual Robotics – Department of Computer Science Whole-Body Collision-Free...
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![Page 1: Laboratory for Perceptual Robotics – Department of Computer Science Whole-Body Collision-Free Motion Planning Brendan Burns Laboratory for Perceptual Robotics.](https://reader035.fdocuments.in/reader035/viewer/2022081515/56649d4d5503460f94a2ca6f/html5/thumbnails/1.jpg)
Laboratory for Perceptual Robotics – Department of Computer Science
Whole-Body Collision-Free Motion Planning
Brendan BurnsLaboratory for Perceptual Robotics
University of Massachusetts Amherst
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2Laboratory for Perceptual Robotics – Department of Computer Science
Why motion planning?
The real world is complicated
Collisions are hazardous
Mobility
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3Laboratory for Perceptual Robotics – Department of Computer Science
How to motion plan?
Configuration space is big! (exponential) Exact methods are intractable Sampling-Based Planning (PRM)
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4Laboratory for Perceptual Robotics – Department of Computer Science
Probabilistic Roadmap PlanningKavraki & Overmars 1996
?
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5Laboratory for Perceptual Robotics – Department of Computer Science
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6Laboratory for Perceptual Robotics – Department of Computer Science
Structure & Exploration
Identify the structure to expect
Acquire knowledge about structure
Exploit understanding as a guide
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7Laboratory for Perceptual Robotics – Department of Computer Science
Models
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8Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Models
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9Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
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10Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Edge Checking
Edge checking is expensive
Our predictive model already exists
Construct a predictive roadmap
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11Laboratory for Perceptual Robotics – Department of Computer Science
Predictive Roadmaps
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12Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
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13Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
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14Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
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15Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
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16Laboratory for Perceptual Robotics – Department of Computer Science
Path Extraction
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17Laboratory for Perceptual Robotics – Department of Computer Science
Experiments
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18Laboratory for Perceptual Robotics – Department of Computer Science
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Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
9-DOF
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19Laboratory for Perceptual Robotics – Department of Computer Science
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Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
12-DOF
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20Laboratory for Perceptual Robotics – Department of Computer Science
Coming Soon…
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21Laboratory for Perceptual Robotics – Department of Computer Science
Stop
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22Laboratory for Perceptual Robotics – Department of Computer Science
Models
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23Laboratory for Perceptual Robotics – Department of Computer Science
Optimal Sampling
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24Laboratory for Perceptual Robotics – Department of Computer Science
Optimal Sampling
?
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25Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
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26Laboratory for Perceptual Robotics – Department of Computer Science
Models
An approximate model of our current understanding
Predicts the state of unobserved configuration-space
Locally Weighted Regression (Atkeson et al.) Others are possible
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27Laboratory for Perceptual Robotics – Department of Computer Science
Active Sampling
Our current understanding suggests areas of improvement
Sample to reduce maximize the expected reduction in model variance (Cohn et al.)
Direct sampling in proportion to complexity