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We use visual data alone to learn a control policy for a robotic arm by observing expert video demonstrations. We implement and test several models, accomplishing an 85% success rate for a pick-and-place task.

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vroom

Learning Robotic Tasks from Video Observation

convlstm usage

checkout alantest branch git checkout alantest

Ensure checkpoints directory exists mkdir -p checkpoints

Data should follow this example structure for train and test directories: ./RoboTurk_videos/bins-Bread/test/demo_XXX_jointdata/frame_XXXX.npy ./RoboTurk_videos/bins-Bread/test/demo_demo_XXX/frame_XXXX.jpg

Modify hyperparameters in trainer_lstm.py

Run trainer script python trainer_lstm.py --folder `realpath RoboTurk_videos/bins-Bread` --name lstm --save_best True --dataset roboturk

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We use visual data alone to learn a control policy for a robotic arm by observing expert video demonstrations. We implement and test several models, accomplishing an 85% success rate for a pick-and-place task.

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