Adding FR5 Embodiments

docs/reproduce.md

@@ -62,8 +62,8 @@ This will automatically create directory under under `scalingup/wandb/` for stor
 The codebase supports domain randomization at data generation time.
 To enable it, add `env/domain_rand_config=all`.
 For example,
-```
-python scalingup/inference.py evaluation.num_episodes=50000 policy=scalingup evaluation=drawer env/domain_rand_config=all
+```sh
+python scalingup/inference.py evaluation.num_episodes=50000 policy=scalingup evaluation=drawer env/domain_rand_config=all env.domain_rand_config.dtd_root=/home/mo/scalingup/dtd/ # `mo` is my dog's name 🐕
 ```
 
 After [running data generation](#data-generation), you can run training using the following command

scalingup/config/common.yaml

@@ -12,6 +12,7 @@ obs_cameras:
  - front
  - top_down
  - ur5e/wsg50/d435i/rgb
+ # - fr5/robotiq_2f85/d435i/rgb
 main_cam: front # this is used in visibility checker
 obs_dim:
   - 160

scalingup/config/evaluation/bin_transport_train.yaml

@@ -5,6 +5,8 @@ sampler_config:
   max_time: 100 # in seconds
 env:
   _target_: scalingup.environment.mujoco.bin_grasping.TableTopBinGraspingMujocoEnv
+  # FR5 + Robotiq85 Env
+  # _target_: scalingup.environment.mujoco.bin_grasping.TableTopBinGraspingFR5Robotiq85MujocoEnv
   bin_x_offset: 0.0
   min_bin_y_dist: 0.22
   max_bin_y_dist: 0.24

scalingup/config/evaluation/table_top.yaml

@@ -6,6 +6,7 @@ sampler_config:
 
 env:
   _target_: scalingup.environment.mujoco.table_top_pick_and_place.TableTopPickAndPlace
+  # _target_: scalingup.environment.mujoco.table_top_pick_and_place.TableTopPickAndPlaceFR5Robotiq85
   obj_instance_configs: []
 
 task_sampler: