deep learning helicopter dynamics models · 2017-03-12 · results on held-out test set stanford...
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![Page 1: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/1.jpg)
Deep Learning Helicopter Dynamics Models
Ali Punjani Pieter Abbeel
UC Berkeley EECS
![Page 2: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/2.jpg)
Latent State: Airflow, Flexibility, Engine Dynamics etc.
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Similar trajectories have similar dynamics
![Page 4: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/4.jpg)
Similar trajectories have similar dynamics
acceleration state-control trajectory
![Page 5: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/5.jpg)
Need similarity and local dynamics
acceleration state-control trajectory
![Page 6: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/6.jpg)
Hierarchical Network Model
Input raw 0.5 second trajectory; Output acceleration
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Hierarchical Network Model
![Page 8: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/8.jpg)
Hierarchical Network Model
Jointly learn partitions of input space and local dynamicsNo labels or annotation
![Page 9: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/9.jpg)
Results on held-out test set
Stanford Autonomous Helicopter Data
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circles ObservedLinear Acceleration ModelReLU Network Model
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flips-loops ObservedLinear Acceleration ModelReLU Network Model
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freestyle-aggressive ObservedLinear Acceleration ModelReLU Network Model
Ground Truth Baseline Model Our Model
![Page 10: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/10.jpg)
60% Improvement across all maneuvers
0 2 4 6 8 10
RMS up-down acceleration error (ms�2)
forward-sideways-flight
orientation-sweeps
vertical-sweeps
stop-and-go
turn-demos1
inverted-vertical-sweeps
orientation-sweeps-with-motion
dodging-demos4
circles
flips-loops
chaos
turn-demos2
dodging-demos3
tictocs
dodging-demos1
dodging-demos2
freestyle-gentle
freestyle-aggressive
turn-demos3
Up-Down Acceleration Error
Linear Acceleration ModelLinear Lag ModelQuadratic Lag ModelReLU Network Model
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Thanks!
![Page 12: Deep Learning Helicopter Dynamics Models · 2017-03-12 · Results on held-out test set Stanford Autonomous Helicopter Data 0 2 4 time (s) 6 8 10 20 10 0 10 20 30 40 Up-Down Acc](https://reader033.vdocuments.us/reader033/viewer/2022053008/5f0be9587e708231d432d3d3/html5/thumbnails/12.jpg)
Similar trajectories have similar dynamics
Apprenticeship Learning (Abbeel, Coates, Ng 2010)