SLIDE 1 Distance Metrics and Algorithms for Task Space Path Optimization
The Robotics Institute Carnegie Mellon University
Rachel Holladay Siddhartha Srinivasa
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Goal: Follow End-Effector Path in Task Space
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Goal: Follow End-Effector Path in Task Space subject to constraints.
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Goal: Follow a Reference Path
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Goal: Follow a Reference Path by leveraging motion planning.
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SLIDE 16 Key Insight Use trajectory optimization to
- ptimize our path to be close
to our reference path.
SLIDE 17 Key Insight Use trajectory optimization to
- ptimize our path to be close
to our reference path.
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Task Space
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Task Space
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Task Space
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Task Space Configuration Space
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Task Space Configuration Space
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Task Space Configuration Space IK FK
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How to compare the distance between task space paths?
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How to compare the distance between task space paths? Borrow from computational geometry.
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One-way Hausdorff Distance
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One-way Hausdorff Distance
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Two-way Hausdorff Distance
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Follow Balls in order.
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Fréchet Distance
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Fréchet Distance
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Fréchet Distance
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Fréchet Distance
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Fréchet Distance
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Fréchet Distance
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Use the Fréchet Distance to capture the task space distance between paths.
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Gradient of Distance Function
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Gradient of Distance Function
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Gradient of Distance Function
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Discrete Fréchet
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How can we assist our optimizer?
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Use our distance metrics to find the areas that need additional constraints.
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SLIDE 62 Key Insight Use trajectory optimization to
- ptimize our path to be close
to our reference path.
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Use computational geometry techniques to measure task space distance between paths.
SLIDE 64 Distance Metrics and Algorithms for Task Space Path Optimization
https://www.personalrobotics.ri.cmu.edu http://www.andrew.cmu.edu/user/rmh/
Rachel Holladay Siddhartha Srinivasa