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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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Why motion planning?
The real world is complicated
Collisions are hazardous
Mobility
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How to motion plan?
Configuration space is big! (exponential) Exact methods are intractable Sampling-Based Planning (PRM)
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Probabilistic Roadmap PlanningKavraki & Overmars 1996
?
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Structure & Exploration
Identify the structure to expect
Acquire knowledge about structure
Exploit understanding as a guide
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Models
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Predictive Models
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Active Sampling
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Predictive Edge Checking
Edge checking is expensive
Our predictive model already exists
Construct a predictive roadmap
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Predictive Roadmaps
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Path Extraction
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Path Extraction
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Path Extraction
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Path Extraction
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Path Extraction
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Experiments
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Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
9-DOF
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Uniform Bridge Active Predictive
Guided Sampling Path ExtractionEdge Validation Collision CheckRoadmap Building
12-DOF
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Coming Soon…
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Stop
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Models
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Optimal Sampling
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Optimal Sampling
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Active Sampling
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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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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
