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Code for "Learning 6-DoF Grasping and Pick-Place Using Attention Focus"
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This is the code for reproducing experiments in the paper, "Learning 6-DoF Grasping and Pick-Place Using Attention Focus". Prerequisites: OpenRAVE, Caffe, 3DNet models, and Matlab with the Python interface (for GPD comparison). Step 1: Run python/test_models_*.py to generate the model files. Step 2: Run python/train_pick_and_place_*.py for joint training of pick and place. Step 3: Run python/train_grasping_*.py for the training grasping only. Step 4: Run python/test_grasping_*.py for testing the trained grasp agent. Step 5: Run python/test_gpd.py to test GPD in the OpenRAVE environment. Files of interest: 1) Reward functions are in the rl_environment_*.py files. 2) HSE3S is implemented in the rl_agent files. 3) The main training files are train_pick_and_place_*.py. 4) The "antipodal" condition is defined in rl_environment_grasping.IsAntipodalGrasp.